COURSE INFORMATION
Biostatistics

 
 
 

BIO111 Introduction to Programming in SAS
WinterSession
Dr. T. Fenton (P), Dr. M. Pagano (S)

1.25 credits
Lectures and Laboratories. Six 4-hour sessions combining both.

Provides an overview in the use of SAS to prepare data for statistical analysis. The focus is on database management and programming problems. Basic issues in each of these areas are discussed in the context of introducing the specific skills required to use SAS effectively.
Course Note: Credit is given for only one of BIO 111 or BIO 113; lab time to be announced at first meeting. Course meets January 10, 11, 12, 17, 18, 19 from 9:30 am to 1 pm. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO113 Introduction to Data Management and Programming in SAS
Fall 1
Ms. L. Allred (P); Dr. M. Pagano (S)

2.5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.

Provides intensive instruction in the use of SAS to prepare data for statistical analysis. The focus is on database management and programming problems. Basic issues in each of these areas are discussed in the context of teaching the specific skills required to use SAS effectively.
Course Note: Credit is given for only one of BIO 111 or BIO 113; BIO 200, BIO 201, or BIO 202 and BIO 203, or BIO 205, or signature of instructor required; lab time to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO200 Principles of Biostatistics
Fall
Dr. R. Betensky

5 credits
Lectures, laboratories. Two 1-hour sessions each week. One 2-hour lab each week.

Lectures and laboratory exercises acquaint the student with the basic concepts of biostatistics and their applications and interpretation. The computer is used throughout the course. Topics include descriptive statistics, graphics, diagnostic tests, probability distributions, inference, tests of significance, association, linear and logistic regression, life tables, and survival analysis.
Course Note: Credit is given for only one of BIO 200, BIO 201 or BIO 205; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students not eligible for BIO 201 or BIO 205. Other students allowed with signature of course instructor, if space permits; course enrollment is limited to 150 students; lab or section times to be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO200R Principles of Biostatistics Repeat
Spring
Dr. R. Betensky

2.5 credits
Independent Study

Open only to students who have failed the core course, and must repeat it. Students must sign up for the section with the instructor from whom they took the original course.
Course Note: Completed independent study contract is required at the time of registration; pass/fail only; signature of instructor required. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO201 Introduction to Statistical Methods
Fall
Dr. K. Gauvreau

5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.

Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health, biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO 200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.
Course Note: Credit is given for only one of BIO 200, BIO 201 or BIO 205; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, and MPH/QM programs. Other students allowed with signature of course instructor, if space permits; lab or section times to be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO201R Introduction to Statistical Methods
Spring
Dr. K. Gauvreau

2.5 credits
Independent Study

Open only to students who have failed the core course, and must repeat it. Students must sign up for the section with the instructor from whom they took the original course.
Course Note: Completed independent study contract is required at the time of registration; pass/fail only; signature of instructor required. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO202 Principles of Biostatistics I
Summer 1
Dr. M. Testa

2.5 credits
Lectures, laboratories. Five 2-hour sessions and five 2-hour labs each week.

This course is the first part of introductory biostatistics and acquaints the student with the basic concepts and methods of biostatistics, their applications, and their interpretation. The material covered includes data presentation, numerical summary measures, rates and standardization, and life tables. Probability is introduced to quantify uncertainty, especially as it pertains to diagnostic and screening methods. Also covered are sampling distributions so that students may be introduced to confidence intervals and hypothesis testing. The computer is used throughout the c ourse, and the student will gain familiarity with the software package STATA.
Course Note: Requires a basic knowledge of mathematics and familiarity with use of personal computers. Students taking BIO202 and BIO203 will not be given credit for BIO200, BIO201 or BIO205. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO203 Principles of Biostatistics II
Summer 2
Dr. P. Park (P), Dr. S. Lagakos (S)

2.5 credits
Lectures, laboratories. Five 2-hour sessions each week and five 2-hour labs each week.

This course is the second part of introductory biostatistics; it continues to explore inference in greater depth. Lectures and laboratory exercises will emphasize applied data analysis, building upon the fundamentals emphasized in BIO 202. Topics covered include the comparison of two means, analysis of variance, non-parametric methods, inference on proportions, contingency tables, multiple 2 X 2 tables, correlation, simple regression, multiple regression and logistic regression, analysis of survival data, and sampling theory. The computer is used throughout the course, and the student will gain more familiarity with STATA.
Course Note: BIO 202 is required; Students who take BIO202 and BIO 203 will not be given credit for BIO200, BIO201 or BIO 205. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO205 Statistical Methods for Health and Social Policy
Fall
Dr. D. Neuberg

5 credits
Lectures, laboratories. Two 1-hour sessions each week. One 2-hour lab each week.

Introduces students to probability and statistics, illustrating their application in the areas of health policy and management and the behavioral sciences. Understanding of basic statistical concepts will be emphasized through problem solving and examples. Topics include: descriptive statistics, diagnostic testing, probability distributions, sampling methods, hypothesis testing, confidence intervals, sample size determination, parametric and non-parametric methods, categorical data and simple linear and logistic regression.
Course Note: Credit is given for only one of BIO 200, BIO 201 or BIO 205; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; Course restricted to students enrolled in HSB, HPM, MPH/HCM, and MPH/LPH programs. Other students allowed with signature of course instructor, if space permits; lab or section times to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO205R Statistical Methods for Health and Social Policy Repeat
Spring
Dr. J. Lindsey (P), Dr. S. Lagakos (S)

2.5 credits
Independent Study

Open only to students who have failed the core course, and must repeat it. Students must sign up for the section with the instructor from whom they took the original course.
Course Note: Completed independent study contract is required at the time of registration; pass/fail only; signature of instructor required. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO206 Introductory Statistics for Medical Research
Summer 1
Dr. E. J. Orav

2.5 credits
Lectures. Five 2-hour sessions each week.

Introduces basic biostatistical techniques with an emphasis on applications to clinical research. Topics include probability and
statistics, hypothesis testing, confidence intervals, non-parametrics, and power calculations.
Course Note: Designed primarily for participants in the Program in Clinical Effectiveness; no auditors.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO207 Statistics for Medical Research II
Summer 2
Dr. G. Reed (P), Dr. E.J. Orav (S)

2.5 credits
Lectures. Five 2-hour sessions each week.

Presents additional biostatistical techniques that commonly appear in the analysis of clinical databases and trials. Topics include contingency table analyses, log-rank tests, paired and matched analyses, analysis of variance and multiple comparisons procedures.
Course Note: BIO 206 required; no auditors.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO208 Statistics for Medical Research, Advanced
Summer 2
Dr. E. J. Orav

2.5 credits
Lectures. Five 2-hour sessions each week.

Presents additional biostatistical techniques that commonly appear in the analysis of clinical databases and trials. This course will move at a faster pace than the alternative BIO 207 while covering all of the same topics (contingency tables, log-rank tests, paired and matched analyses, analysis of variance and multiple comparisons procedures). In addition, linear and logistic regression will be introduced.
Course Note: BIO 206 required; no auditors.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO209 Statistics for Medical Research, Translational
Summer 2
Dr. M. Wang

2.5 credits
Lectures. Five 2-hour sessions each week.

Presents additional biostatistical techniques that are most relevant to researchers involved with designed experiments. Topics include contingency tables, paired analyses, simple analysis of variance, multiple comparisons procedures, two-way analysis of variance, and simple repeated measures analysis of variance.
Course Note: BIO 206 required; no auditors.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO210 The Analysis of Rates and Proportions
Spring
Dr. G. DiRienzo

5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 1.5-hour lab each week.

Emphasizes concepts and methods for analysis of data which are categorical, rate-of-occurrence (e.g., incidence rate), and time-to-event (survival duration). Stresses applications in epidemiology, clinical trials, and other public health research. Topics include measures of association, 2x2 tables, stratification, matched pairs, logistic regression, model building, analysis of rates, and survival data analysis using proportional hazards models.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 205, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO211 Regression and Analysis of Variance in Experimental Research
Spring
Dr. M. Shih

5 credits
Lectures, laboratories. Two 1.5-hour sessions each week; one 1-hour lab each week.

Covers analysis of variance and regression, including details of data-analytic techniques and implications for study design. Also included are probability models and computing. Students learn to formulate a scientific question in terms of a statistical model, leading to objective and quantitative answers.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 205, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO212 Survey Research Methods In Community Health
Spring
Dr. T. Mangione (P), Dr. S. Lagakos (S)

2.5 credits
Lectures. One 2-hour session each week.

Covers research design, sample selection, questionnaire construction, interviewing techniques, the reduction and interpretation of data, and related facets of population survey investigations. Focuses primarily on the application of survey methods to problems of health program planning and evaluation. Treatment of methodology is sufficiently broad to be suitable for students who are concerned with epidemiological, nutritional, or other types of survey research.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO213 Applied Regression for Clinical Research
Fall
Dr. E. J. Orav

5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.

This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 205, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO214 Principles of Clinical Trials
Spring 1
Dr. D. Wypij

2.5 credits
Lectures. Two 2-hour sessions each week.

Designed for individuals interested in the scientific, policy, and management aspects of clinical trials. Topics include types of clinical research, study design, treatment allocation, randomization and stratification, quality control, sample size requirements, patient consent, and interpretation of results. Students design a clinical investigation in their own field of interest, write a proposal for it, and critique recently published medical literature.
Course Note: BIO 200, or BIO 201, or BIO202 and BIO203, or BIO205, or BIO206 and one of BIO 207, BIO 208 or BIO 209, or signature of instructor required.


Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO214 Principles of Clinical Trials
Summer 2
Dr. K. Stanley, Dr. R. Gelber

2.5 credits
Lectures. Five 2-hour sessions each week.

Designed for individuals interested in the scientific, policy, and management aspects of clinical trials. Topics include types of clinical research, study design, treatment allocation, randomization and stratification, quality control, sample size requirements, patient consent, and interpretation of results. Students design a clinical investigation in their own field of interest, write a proposal for it, and critique recently published medical literature.
Course Note: Signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO222 Basics of Statistical Inference
Fall
Dr. Yi Li

5 credits
Lectures, laboratories. Two 1.5 hour-sessions each week. One 2-hour lab each week.

This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.
Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO223 Applied Survival Analysis and Discrete Data Analysis
Spring
E. Goetghebeur, E.A. Houseman

5 credits
Lectures. Two 2-hour sessions each week. One 1-hour optional lab each week.

This course will cover topics in both discrete data analysis (25% of class) and applied survival analysis (75% of class). The course will begin with a review of sampling plans and contingency table for discrete data. Further topics in discrete data analysis will include logistic regression, exact inference, and conditional logistic regression. This short survey of discrete data topics will provide a natural transition to analysis of survival data. Survival topics include: hazard, survivor, and cumulative hazard functions, Kaplan-Meier and actuarial estimation of the survival distribution, comparison of survival using log rank and other tests, regression models including the Cox proportional hazards model and accelerated failure time model, adjustment for time-varying covariates, and use of parametric distributions (exponential, Weibull) in survival analysis. Class material will include presentation of statistical methods for estimation and testing, along with current software (SAS, Stata, Splus) for implementing analyses of discrete data and survival data. Applications to real data will be emphasized.
Course Note: BIO 210 and BIO 213, or BIO 230 required, or signature of instructor. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO224 Survival Methods in Clinical Research
Summer 2
Dr. R. Davis

2.5 credits
Lectures. Five 2-hour sessions each week.

This course will cover the common approaches to the display and analysis of survival data, including Kaplan-Meier curves, log rank tests, and Cox proportional hazards regression. Computing, using SAS, will be an integral component of the course.
Course Note: BIO 210, BIO 211, BIO 213 or signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO226 Applied Longitudinal Analysis
Fall
Dr. J. Ware

5 credits
Lectures, laboratories. Two 2-hour sessions each week.

This course covers modern methods for the analysis of repeated measures, correlated outcomes and longitudinal data, including the unbalanced and incomplete data sets characteristic of biomedical research. Topics include an introduction to the analysis of correlated data, repeated measures ANOVA, random effects and growth curve models, and generalized linear models for correlated data, including generalized estimating equations (GEE).
Course Activities: Homework assignments will focus on data analysis in SAS using PROC GLM, PROC MIXED, and PROC GENMOD.
Course Note: BIO 211, BIO 213, or BIO 232, or signature of instructor required; lab or section times will be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO227 Fundamental Concepts in Gene Mapping
Fall 2
Dr. P. Kraft, Dr. C. Lange

2.5 credits
Lectures, laboratories. Two 2-hour sessions each week.

This course introduces students to the diverse statistical methods used throughout the process of genetic pidemiology, from familial aggregation and segregation studies to linkage scans and candidate-gene association studies. Topics covered include multipoint and model-free linkage analysis, linkage disequilibrium, family-based and population-based association tests, and study design. Instructors use ongoing research into the genetics of asthma and cancer to illustrate basic principles. Homework includes analysis projects to familiarize students with state-of-the-art software for linkage analysis, family-based association tests, and case-control studies. Some familiarity with molecular biology and statistical hypothesis testing (e.g. material covered in EPI249 and BIO201) is helpful, although not necessary, as relevant concepts will be reviewed in lectures and labs. Students should leave with a basic understanding of how to read and evaluate statistical studies of genetic epidemiology.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO228 Statistical Genetics in Complex Human Disease
Spring 1
Dr. C. Lange, Dr. P. Kraft

2.5 credits
Lectures, laboratories. Two 2-hour sessions each week.

This course concentrates on the design and analysis of complex-disease association studies. It starts with a review of key concepts in genetic epidemiology (population genetics, population stratification, linkage disequilibrium, "tagging" SNPs) and then proceeds in two parts: population-based studies and family-based studies. Each part covers problems of design and analysis, among them: choice of test statistic, inferring and analyzing phased haplotypes from unphased genotypes, multiple comparisons, and gene-environment interactions. Homework consists of two analysis projects (one population-based and one family-based) designed to give students hands-on experience with current applications and software.
Course Note: BIO227 or signature of instructor required.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO230 Probability Theory and Applications I
Fall
Cross listed at FAS as BIST230

Dr. M. Pagano
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.

Axiomatic foundations of probability, independence, conditional probability, joint distributions, transformations, moment generating functions, characteristic functions, moment inequalities, sampling distributions, modes of convergence and their interrelationships, laws of large numbers, central limit theorem, and stochastic processes.
Course Note: Enrollment in the Biostatistics department, or BIO 222, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed: HSPH student must register for HSPH course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO231 Statistical Inference I
Spring
Cross-listed as FAS as BIST231

Dr. V. DeGruttola
5 credits
Lectures, laboratories. Two 2-hour sessions each week. One 1.5-hour lab each week.

A fundamental course in statistical inference. Discusses general principles of data reduction: exponential families, sufficiency, ancillarity and completeness. Describes general methods of point and interval parameter estimation and the small and large sample properties of estimators: method of moments, maximum likelihood, unbiased estimation, Rao-Blackwell and Lehmann-Scheffe theorems, information inequality, asymptotic relative efficiency of estimators. Describes general methods of hypothesis testing and optimality properties of tests: Neyman-Pearson theory, likelihood ratio tests, score and Wald tests, uniformly and locally most powerful tests, asymptotic relative efficiency of tests.
Course Note: BIO 230 or signature of instructor required; lab or section time to be announced at first meeting; cross-listed: HSPH student must register for HSPH course. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO232 Methods I
Fall
Cross-listed at FAS as BIST232

Dr. B. Coull
5 credits
Lectures. Two 2-hour sessions each week.

Introductory course in the analysis of Gaussian and categorical data. The general linear regression model, ANOVA, robust alternatives based on permutations, model building, resampling methods (bootstrap and jackknife), contingency tables, exact methods, logistic regression.
Course Note: Enrollment in the Department of Biostatistics, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed: HSPH student must register for HSPH course.





Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO233 Methods II
Spring
Dr. R. Gray, Dr. L.J. Wei

5 credits
Lectures, laboratories (optional). Two 2-hour sessions each week. One 1.5-hour lab each week.

Intermediate course in the analysis of Gaussian, categorical, and survival data. The generalized linear model, Poisson regression, random effects and mixed models, comparing survival distributions, proportional hazards regression, splines and smoothing, the generalized additive model.
Course Note: BIO 232, or signature of instructor required; lab or section times to be announced at first meeting.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO234 Research Synthesis & Meta-Analysis in Public Health & Medicine
Summer 2
Dr. M. Stoto

2.5 credits
Lectures. Five 2-hour sessions each week.

Concerned with the use of existing data to inform clinical decision making and health care policy, the course focuses on research synthesis (meta-analysis). The principles of meta-analytic statistical methods are reviewed and the application of these to data sets is explored. Application of methods includes considerations for clinical trials and observational studies. The use of meta-analysis to explore data and identify sources of variation among studies is emphaiszed, as is the use of meta-analysis to identify future research questions.
Course Activities: Students prepare a protocol to conduct a meta-analysis and use existing meta-analysis software to apply principles outlined in the course to data sets provided for this purpose.
Course Note: This course is equivalent to EPI233; credit will not be given for both courses. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO235 Regression and Analysis of Variance
Fall
Instructor to be announced

5 credits
Course not offered 2005-2006.
Lectures, laboratories. Two 2-hour sessions each week. One 2-hour lab each week.

This is an advanced course in data analysis for linear models - regression and analysis of variance. Estimation methods (maximum likelihood and least squares) and issues of inference (confidence intervals, hypothesis testing, analysis of residuals) are presented from a theoretical and data analysis perspective. Background in matrix algebra and linear regression required.
Course Note: BIO230 and BIO232, or signature of instructor required; lab or section times to be announced at first meeting; cross-listed, HSPH student must register for HSPH course. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO243 Nonparametric Methods
Spring 1
Dr. M. Hughes

2.5 credits
Course not offered 2005-2006; offered alternate years.
Lectures. Two 2-hour sessions each week.

Presents the theory and application of nonparametric methods. Topics include permutation tests, permutation limit theorems, 2-sample rank tests and their asymptotic efficiency, k-sample rank tests, 1-sample tests of location, paired comparisons, rank tests for symmetry and independence, and analogues of linear modeling based on ranks.
Course Note: BIO231 required.


Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO244 Analysis of Failure Time Data
Fall
Dr. S. Lagakos

5 credits
Lectures. Two 2-hour sessions each week.

Discusses the theoretical basis of concepts and methodologies associated with survival data and censoring, nonparametric tests, and competing risk models. Much of the theory is developed using counting processes and martingale methods. Material is drawn from recent literature.
Course Note: BIO 231 and BIO 233 required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO245 Analysis of Multivariate and Longitudinal Data
Fall
Dr. P. Williams

5 credits
Lectures. Two 2-hour sessions each week.

Presents classical and modern approaches to the analysis of multivariate observations, repeated measures, and longitudinal data. Topics include the multivariate normal distribution, Hotelling's T2, MANOVA, the multivariate linear model, random effects and growth curve models, generalized estimating equations, statistical analysis of multivariate categorical outcomes, and estimation with missing data. Discusses computational issues for both traditional and new methodologies.
Course Note: BIO 231 and BIO 235 required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO247 Design of Scientific Investigations
Spring
Dr. M. Hughes

5 credits
Course not offered 2005-2006; offered alternate years.
Lectures. Two 2-hour sessions and one 2-hour lab each week.

Discusses those aspects of statistical theory and practice relevant to the design of scientific investigations in the health sciences. Topics include sample size considerations, basic principles of experimental design (randomization, replication, and balance), block designs, factorial experiments, response surface modeling, clinical trials, adaptive designs, cohort studies, early detection trials, and double sampling techniques.
Course Note: BIO 235 or signature of instructor required; minimum enrollment of 10 students required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO248 Advanced Statistical Computing
Spring
Dr. P. Catalano

5 credits
Lectures. Two 2-hour sessions each week.

A course in computing algorithms useful in statistical research and advanced statistical applications. Topics include computer arithmetic, matrix algebra, numerical optimization ethods with application to maximum likelihood estimation and GEEs, spline smoothing and penalized likelihood, numerical integration, random number generation and simulation methods, Gibbs sampling, bootstrap methods, missing data problems and EM, imputation, data augmentation algorithms, and Fourier transforms. Students should be proficient with C or Fortran programming.
Course Note: BIO235, or signature of instructor required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO249 Bayesian Methods in Biostatistics
Fall
Dr. S. Normand

5 credits
Course not offered 2005-2006.
Lectures. Two 2-hour sessions each week.

This course examines basic aspects of the Bayesian paradigm including Bayes theorem, decision theory, general principles (likelihood, exchangeability, de Finetti's theorem), prior distributions (conjugate, non-conjugate, reference), single-parameter models (binomial, poisson, normal), multi-parameter models (normal, multinomial, linear regression, general linear model, hierarchical regression), inference (exact, normal approximations, non-normal approximations, non-normal iterative approximations), computation (Monte Carlo, convergence diagnostics), model diagnostics (Bayes factors, predictive ordinates), design, and empirical Bayes methods.
Course Note: BIO231 and BIO232, or signature of instructor required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO250 Probability Theory and Applications II
Spring
Dr. A. Rotnitzky

5 credits
Lectures. Two 2-hour sessions each week.

Basic set theory, measure theory, Riemann-Stieltjes and Lebesgue integration, conditional probability, conditional expectation (projection), martingales, Radon-Nikodym derivative, product measure and Fubini's Theorem, limit theorems on sequences of random variables, stochastic processes, weak convergence.
Course Note: BIO 230 and BIO 232, or signature of instructor required; cross-listed, HSPH student must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO251 Statistical Inference II
Spring
Dr. T. Cai

5 credits
Lectures. Two 2-hour sessions each week.

Sequel to BIO 231. Considers several advanced topics in statistical inference. Topics include limit theorems, multivariate delta method, properties of maximum likelihood estimators, saddlepoint approximations, asymptotic relative efficiency, robust and rank-based procedures, resampling methods, and nonparametric curve estimation.
Course Note: BIO 231 required; cross-listed, HSPH must register for HSPH course
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO262 Statistical Problems in Drug Development
Fall
Dr. M. Testa

2.5 credits
Course not offered 2005-2006; offered alternate years.
Lectures. One 2-hour session each week.

This course will introduce the student to the "real life" applications of statistical methodology required for pharmaceutical drug development and will feature guest lecturers from the pharmaceutical industry. Weekly seminars will cover statistical techniques used in the various phases of drug development, including assessment of pharmacologic activity; preclinical animal models and toxicology studies; clinical trials (Phase I dose ranging through Phase III comparative efficacy trials); and post-surveillance, pharmacoepidemiologic and pharmacoeconomic studies. Statistical techniques and examples include applications of optimum screening designs, use of non-parametric estimators, problems of multiplicity, tests for monotonicity, parametric and nonparametric regression, ordered categorical data analysis, survival methods, issues of power and sample size, bioequivalence studies, longitudinal data analysis, univariate and multivariate general linear models, multiple endpoint problems and quality-of-life measurement models. Exposure to
linear models and non-parametric statistics recommended.
Course Note: BIO 210, BIO 211 or BIO 213 or signature of the instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO263 Computational Methods for Categorical Data Analysis
Spring 2
Dr. C. Mehta

2.5 credits
Course not offered 2005-2006; offered alternate years.
Lectures. Two 2-hour sessions each week.

This course deals with exact nonparametric methods of inference. These methods use fast numerical algorithms to permute the observed data in all possible ways, and thereby derive exact distributions for the test statistics of interest without making any distributional or large-sample assumptions. In contrast, standard parametric methods of inference make distributional assumptions about the data, while standard nonparametric methods of inference rely on asymptotic theory to derive approximate distributions for the test statistics. Exact nonparametric methods are particularly important for small, sparse or unbalanced data where the usual asymptotic theory breaks down. This course will cover exact inference for one, two and K-sample problems, ordered and unordered RxC contingency tables, 2x2 and 2xC contingency tables with or without stratification, and logistic regression. A unified view, encompassing both continuous and categorical data, will be presented based on the permutation principle. Modern algorithmic advances that make exact permutational inference computationally feasible will be treated in depth. The methods will be illustrated by several biomedical data sets. This course will use StatXact and LogXact statistical packages.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO268 Seminar on Statistical Methods in Human Genetics
Spring 2
Dr. N. Laird

2.5 credits
Lectures, laboratories. Two 1.5-hour sessions each week. One 1-hour lab each week.

This course provides a self-contained introduction to statistical genetics. Emphasis is placed on modern methods for gene mapping. Topics include Hardy-Weinberg disequilibrium, estimation of allele frequencies, linkage analysis, association analysis and haplotypes. Genetic concepts will be introduced as necessary.
Course Note: BIO222 and BIO228, or BIO230, or signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO270 Statistical Science Outreach
WinterSession
Dr. R. Gelman, Dr. M. Hughes

2.5 credits
To be given 2005-2006; offered alternate years.
Seminars. Sixteen 2-hour sessions during WinterSession.

This is a seminar aimed at broadening the background of students in probability and statistics. Students will be expected to give short presentations from expository articles and papers. Articles will be chosen on the basis of ideas rather than technical content. There will be some emphasis on historical developments. This course is suitable for students in any year of the Biostatistics program.
Course Note: Enrollment in a biostatistics degree program required; this class cannot be used to satisfy the intermediate requirement for doctoral students in the Department of Biostatistics; Pass/Fail grading option only, minimum enrollment of 10 students required; signature of instructor required; Course meets 10:30 am to 12:30 pm.


Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO271 Statistical Computing Environments
Fall
Dr. W. Wang

2.5 credits
Lectures, laboratories. One 2-hour session each week.

Acquaints the students with the modern computing environments (hardware and software) needed for careers in biostatistics. Course will consist of lectures and computer labs, with several guest lecturers. Specific topics include, programming environments in statistics, algorithmic and symbolic mathematics, source language programming and its tools, editors,
typesetters, Internet tools, UNIX and other tools that have great potential for research in and practice of statistics.
Course Note: Enrollment in a biostatistics degree program required; this class cannot be used to satisfy the intermediate requirement for doctoral students in the Department of Biostatistics; no auditors.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO275 Operational Mathematics
Fall
Dr. C. Hu

2.5 credits
Lectures. One 2-hour session each week.

The aim of this course is to strengthen students' background in analysis and operational use of mathematics. The course will emphasize the application of several fundamental results, and not the proofs of these results. Students will work several problems which illustrate fundamental mathematical operations. Topics include concepts of convergence (e.g., power series, Taylor's series), functions (limits, continuity, step functions, L'Hopital's rule, differentiability), integration (Riemann, Stieltjes, Lebesque), operations convergence theorem, complex variables (e.g., Laplace transforms, Fourier transforms, inversion formulas).
Course Note: Enrollment in the Biostatistics Department, or signature of instructor required. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO276 Sequential Analysis
Spring
Dr. C. Mehta

2.5 credits
To be given 2005-2006; offered alternate years
Lectures. One 2-hour session each week.

This course will cover the basic theory underlying the design and interim monitoring of group sequential clinical trials and will illustrate the theory with examples of real clinical trials. Topics include: distribution theory for stochastic processes with independent increments; the recursive integration algorithm; stopping boundaries and error spending functions; maximum information trials; conditional power and stochastic curtailment; repeated confidence intervals; inference following group sequential testing; sample size re-estimation; more general adaptive
designs. Software support for this course will be provided by East software.
Course Note: BIO 230 or signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO277 Computational Biology
Spring
Dr. C. Li

5.0 credits
Course not offered 2005-2006
Lectures. One 4-hour session each week.

A graduate level introduction to computational molecular biology for students with quantitative background. The topics include: review of biology, gene expression microarray, sequence and cis-regulatory analysis, special topics and class project presentations.
Course Note: BIO 231, or signature of instructor required; ordinal grading option only; cross-listed course HSPH student must register for HSPH course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO280 Introduction to Computational Molecular Biology
Spring
Dr. X. Liu

5 credits
Lectures, laboratories. Two 1.5-hour sessions each week.

Graduate entry level course to basic problems, algorithms and data analysis methods in computational biology. Topics covered in the course include sequence alignment, gene finding and annotation, microarray analysis, gene regulatory network, RNA/protein structure prediction, proteomics and pharmacogenetics. The course is targeted towards graduate students and postdocs in Biostatistics Department and Division of Biological Sciences.
Course Note: Lab or section will be announced at first meeting; cross-listed course, HSPH students must register for HSPH course. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO284 Spatial Statistics for Health Research
Fall 2
Dr. L. Ryan, Dr. Y. Li

2.5 credits
Not to be given 2005-2006; offered alternate years.
Lectures, seminars. Two 2-hour sessions each week.

This course will introduce students to a broad range of topics in spatial statistics, including but not limited to types of spatial data, kriging, parametric and non-parametric methods, tests for spatial randomness. The course will draw on many real examples. Students will become proficient in the use of Splus SpatialStats and ArcGIS
Course Activities: Homework assignments, project and class presentation.
Course Note: Minimum enrollment of 10 students; instructor's signature required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO287 Public Health Surveillance
Spring
Dr. A. Ozonoff

2.5 credits
Not to be given 2005-2006; offered alternate years.
Lectures. One 2-hour session each week.

Surveillance is an important component of public health. Its function is to detect and monitor disease incidence and it has three components: to collect data, to analyze it, and to report the results. This course considers all three aspects with particular emphasis on the analysis of surveillance data. We shall consider both the more traditional surveillance systems, where data collection and reporting are done at a relatively leisurely pace, and systems that provide for immediate feedback and thus are designed to detect biological terrorism and other situations where rapid response is desirable. We shall study both passive and active surveillance systems. Statistical techniques covered include time series, clustering methods, and other geo-temporal techniques.
Course Note: BIO 232, or signature of instructor required; no auditors. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO288 Semiparametric Methods for Analysis of Missing and Censored Data
Spring
Dr. A. Rotnitzky

2.5 credits
Not to be given 2005-2006; offered alternate years.
Lectures. One 2-hour session each week.

The goal of the course is to provide a comprehensive discussion of optimal estimation techniques for low dimensional parameters of semiparametric models (i.e. models with infinite dimensional nuisance parameters) for complex longitudinal data subject to informative censoring or missingness. The course will start with the discussion of the fundamental notions and results of semiparametric theory: pathwise derivatives, tangent space, semiparametric variance and information bounds, and influence functions. It will then provide a general estimating function methodology for locally semiparametric efficient estimation and doubly robust estimation under data that are coarsened at random. This general methodology will then be applied to derive locally efficient doubly robust estimators of 1) regression parameters in multivariate generalized linear models subject to missing at random data, 2) the survival function of an endpoint subject to dependent right censoring, 3) the quality of life adjusted survival time subject to dependent right censoring 4) the survival function of multivariate failure time data subject to univariate (dependent) censoring, 5) Cox regression parameters based on dependent right censored data and 6) smooth parameters of the distribution of a time to an endpoint outcome based on current status data and interval censored data.
Course note: BIO231, BIO244, and BIO250 or signature of instructor required. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO289 Reading the Medical Literature: A Course for Statisticians
WinterSession
Dr. D. Neuberg

1.25 Credits
Course not offered 2005-2006
Seminars. Eight 2-hour sessions.

The goal of this course is to offer students the opportunity to improve their skills at critical reading of the medical literature. Papers will be approached from a statistical point of view, and discussion will focus how to identify the structure of the clinical study, including the statistical design, from the ultimate published report of results. Papers will be drawn from the recent medical literature, with an emphasis on publications appearing in the New England Journal of Medicine, Lancet, and other journals of similar nature. For each paper, one student will summarize the content of the paper, and a second student will critique the paper. All students are expected to read every paper, and be prepared to participate in classroom discussion.
Course note: Registration will be limited to students enrolled in a degree program in Statistics or Biostatistics; pass/fail grading option only. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO300 Independent Study/ Tutorial
Fall 1
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. These programs are open to all students who wish to go beyond the content of the regular courses.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required.


BIO300 Independent Study/ Tutorial
Fall
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
Fall 2
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
Spring 1
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
Spring
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
Spring 2
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
WinterSession
Department Members

Time and credit to be arranged.

An opportunity for independent study is offered for interested and qualified students or small groups of students. Arrangements must be made with individual faculty members and are limited by the amount of faculty time available. Theses programs are open to all students who wish to go beyond the content of regular courses.
Course Note: Completed independent study/ tutorial contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail grading option only.


BIO300 Independent Study/ Tutorial
Summer
Department Members

Time and credit to be arranged.

Guided study in specific areas of statistical methodology and applications.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO300 Independent Study/ Tutorial
Summer 2
Department Members

Time and credit to be arranged.

Guided study in specific areas of statistical methodology and applications.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Fall 1
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Fall
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Fall 2
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Spring 1
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Spring
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Spring 2
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Summer 1
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Summer
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO311 Teaching
Summer 2
Dr. D. Wypij

Time and credit to be arranged.

Work with members of the department in laboratory instruction and the development of teaching materials.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term.


BIO312 Consultation
Fall
Dr. M. Hughes

Time and credit to be arranged.

Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO312 Consultation
Spring
Dr. M. Hughes

Time and credit to be arranged.

Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO312 Consultation
Summer 1
Department Members

Time and credit to be arranged.

Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO312 Consultation
Summer
Department Members

Time and credit to be arranged.

Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO312 Consultation
Summer 2
Department Members

Time and credit to be arranged.

Work with members of the department on current statistical consultation activities.
Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO313 Computing
Fall
Dr. D. WYpij

Time and credit to be arranged.

Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO313 Computing
Spring
Dr. D. Wpij

Time and credit to be arranged.

Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO313 Computing
Summer
Department Members

Time and credit to be arranged.

Course Note: Completed independent study contract is required at the time of registration; maximum of 5 credits per independent study topic; pass/fail only; signature of instructor required; students may register for a maximum of 5 credits in the summer term. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO350 Research
Fall 1
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Fall
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Fall 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Spring 1
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Spring
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Spring 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
WinterSession
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Summer 1
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Summer
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO350 Research
Summer 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Fall 1
Department Members

Time and credit to be arranged.
For doctoral candidates who have passed their school-wide Oral Qualifying
Examination and who are undertaking advanced work along the lines of
fundamental or applied research in the department.
Course Note: Pass/Fail only; maximum of 20 credits; signature of
instructor required.


BIO400 Non-Resident Research
Fall
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.




BIO400 Non-Resident Research
Fall 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Spring 1
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Spring
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Spring 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
WinterSession
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Summer 1
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Summer
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO400 Non-Resident Research
Summer 2
Department Members

Time and credit to be arranged.

For doctoral candidates who have passed their school-wide Oral Qualifying Examination and who are undertaking advanced work along the lines of fundamental or applied research in the department.
Course Note: Pass/fail only; maximum of 20 credits; signature of instructor required.


BIO501 Linear and Longitudinal Regression
Summer 2
Dr. G. Fitzmaurice

2.5 credits
Lectures, laboratories. 5 1.75-hour sessions each week.

This course is intended for students who are already very comfortable with fundamental techniques in statistics. The course will cover methods for building and interpreting linear regression models, including statistical assumptions and diagnostics, estimation and testing, and model building techniques. Repeated measures and random effects will be introduced into these models to account for experimental designs that involve correlated responses. Lectures will be accompanied by computing exercises using the SAS statistical package.
Course Note: BIO 200, or BIO201, or BIO205, or BIO BIO206, or BIO202 and BIO203 is required. Ordinal grading option only. Lab or section will be announced at first meeting. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


BIO503 Introduction to Programming and Statistical Modeling in R
WinterSession
Dr. J. Harezlak, Dr. C. Paciorek, Dr. E.A. Houseman

1.25 credits
Seminars. Five 3-hour sessions during WinterSession


This course is an introduction to R, a powerful and flexible statistical language and environment that also provides more flexible graphics capabilities than other popular statistical packages. The course will introduce students to the basics of using R for statistical programming, computation, graphics, and modeling. We will start with a basic introduction to the R language, reading and writing data, and graphics. We then discuss writing functions in R and tips on programming in R. Finally, the latter part of the course will focus on using R to fit some important types of statistical models, including linear regression, generalized linear models, generalized additive models, and mixed effects models.

Our goal is to get students up and running with R such that they can use R in their research and are in a good position to expand their knowledge of R on their own. Basic knowledge of statistics at the level of a basic understanding of linear regression is required.
Course Note: Pass/fail grading option only


ID253 Information Management in Epidemiology
Spring 1
Department of Epidemiology and the Department of Biostatistics

Dr. K. A. Chan, Dr. M. Testa
Course not offered 2005-2006
2.5 credits
Lectures, case studies, computer exercises. Two 2-hour sessions each week with optional computer lab sessions.

This course is designed to introduce students to the theory and applications of information technology that are used in modern epidemiology. Pertinent concepts of relational database theory and structured query language will be described, followed by lectures on data forms design, database construction, and data validation for studies that involve ad hoc collection of primary data. Record linkage techniques for utilization of secondary data in epidemiology will be introduced. Existing data sources, such as Medicaid, automated insurance claims systems, and computerized medical records will be described. Students will have hands-on experience working with computer programs in the lab sessions. Examples will be drawn from studies in pharmacoepidemiology, clinical epidemiology, and intervention studies.
Course Note: Introduclevel courses in epidemiology are strongly recommended.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


ID265 Practice of Quantitiative Methods
Spring 1
Department of Biostatistics and the Master of Public Health Program

Dr. M. Testa, D. Simonson
2.5 credits
Lectures, seminars, case studies. Two 2-hour sessions each week.

Explores practical and conceptual issues in the design, conduct, analysis and evaluation of human studies through the discussion of current research and methodologies. Students design studies to address important health problems. Class discussion and group projects are emphasized.
Course Note: Acceptance into the MPH concentration in Quantitative Methods or signature of instructor required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


ID270 Summer MPH Practicum and Culminating Experience for CLE
WinterSession
Dr. E. Cook

5.0 credits
Seminars. Five 1- to 2- hour sessions each week.

Summer-Only CLE Master of Public Health Program students develop an off-site practicum at their home institution under the supervision of a local mentor and member of the faculty at HSPH. This practicum may include aspects of epidemiology, biostatistics, decision sciences, or other quantitative aspects of public health. Students should apply the competencies learned in core courses to an actual investigation. Following the first summer course work, students must submit a written proposal for the practicum along with a letter of support from an investigator from the student's home site, indicating an agreement to act as the local mentor for the project. This proposal is reviewed and an HSPH faculty supervisor is identified. Students ordinarily would write a paper suitable for publication, a grant proposal or a technical report. Noramlly this exercise culminates with a presentation in the final summer of the student's program. However, if the project is not completed at that time, the presentation can be delayed to the following WinterSession. In this situation, the student would still attend the seminar of presentations during the Summer Session but would register for this course in the WinterSession.
Course Note: Students must attend the sessions of this course during the second and third summer and they are encouraged to attend their first summer. Regular contact between students and mentors and among students is expected via e-mail during the year to seek advice, provide activity updates and to discuss approached to the solution of methodological issues; instructor's signature required, contract required, pass/fail grading option only.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


ID509 Functional Genomics, Proteomics and Bioinformatics
WinterSession
Department of Genetics and Complex Diseases, Department of Nutrition and Department of Biostatistics

Dr. M. Wessling-Resnick, Dr. D. Wolf, and Dr. S. Liu
2.5 credits
Lectures, seminars, case studies.

This interdisciplinary course is intended for students who have background knowledge of molecular biology and are interested in the application of genomics and proteomics to their research. The course will introduce basic bioinformatic applications for genome sequence analysis (BLAST), use of CLUSTAL-W, basic methods in DNA sequence acquisition and DNA expression analysis by microarray, use of genomic information in the public health arena, basic methods and application of proteome analysis and the demonstration of proteomic research tools.
Course notes: HSPH degree candidates only; ordinal grading option only: instructor's signature required. Meets on Monday, Wednesday, Thursday and Friday, 9 am to 12 pm during WinterSession. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


RDS280 Decision Analysis for Health and Medical Practices
Fall 2
Department of Health Policy and Management and the Department of Biostatistics

Dr. S. Goldie
2.5 credits
Lectures. Two 2-hour sessions each week.

This course is designed to introduce the student to the methods and growing range of applications of decision analysis and cost-effectiveness analysis in health care technology assessment, medical decision making, and health resource allocation. The objectives of the course are: (1) to provide a technical understanding of the methods used, (2) to give the student an appreciation of the practical problems in applying these methods to the evaluation of clinical interventions and public health policies, and (3) to give the student an appreciation of the uses and limitations of these methods in decision making at the individual, organizational, and policy level both in developed and developing countries.
Course Note: Introductory course in probability and statistics required; BIO200, BIO201, or BIO203 may be taken concurrently; introductory economics is recommended but not required.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


RDS282 Cost-Effectiveness and Cost-Benefit Analysis for Hlth Prog. Eval
Spring 1
Department of Health Policy and Management and Department of Biostatistics

Dr. M. Weinstein
2.5 credits
Lectures, seminars. Two 2-hour sessions each week.

Provides an introduction to methods for economic evaluation of health and environmental programs, including theory and applications. Topics include theory of benefit-cost and of cost-effectiveness analysis, definition and methods for estimating costs, stated-preference and revealed-preference methods for valuing health and mortality risk, quality adjusted life years.
Course Note: Introductory decision analysis (e.g. RDS280, HPM286) and economics (e.g. HPM205, HPM206) are recommended. Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.


RDS285 Decision Analysis Methods in Public Health and Medicine
Spring 2
Department of Health Policy and Management and the Department of Biostatistics

Dr. L. Prosser (P), Dr. M. Weinstein (S)
Lectures, seminars, lab. Two 2-hour sessions each week, one 1-hour lab.

An intermediate-level course on methods and health applications of decision analysis and other modeling techniques. Topics include Markov models, life expectancy modeling, deterministic and probabilistic sensitivity analysis, simulation models, ROC analysis and diagnostic technology assessment, quality of life valuation, multi-attribute utility, and behavioral decision theory.
Course Note: RDS 280, RDS 286, or equivalent introductory course on decision analysis required or signature of instructor required; familiarity with matrix algebra and elementary calculus may be helpful but not required; lab or section times to be announced at first meeting.




Last modified:03/28/2006 16:22:04

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