Schedule 

Lectures
Wednesday 12:20 - 13:50 K2  
Exercise Class
Wednesday 14:00 - 15:30 K10A  

Course Contents 

  1. February 21
    Role of statistics in medical research. Subject of epidemiology. Prevalence, incidence of disease. Estimating incidence by piecewise exponential model.
    Supplementary reading:
    [EBR], Chap. 1, pp. 1–34, [BD1] Chap. II, pp. 42–47.
  2. February 28
    Age-specific incidence. Age-standardized incidence. Cumulative incidence. Confidence intervals for age-standardized and cumulative incidence.
    Supplementary reading:
    [EBR], Chap. 2, pp. 49–62, [BD1] Chap. II, pp. 47–54, [BD2] Chap. 2, pp. 48–61.
  3. March 7
    Exposures. Relative risk, excess risk. Estimating relative risk from aggregated data. Analysis of binary exposures (2 x 2 tables). Cohort and case-control design. Invariance of odds ratio to study design. Relationship between odds ratio and relative risk. Small sample methods for estimating odds ratio.
    Supplementary reading:
    [BD1] Chap. II, pp. 53–73, Chap. IV, pp. 122–129.
  4. March 14
    Large sample methods for estimating odds ratio. Control of confounding in case-control studies: sampling and analytic strategies. Stratification, matching, adjustment. Analysis of stratified case-control studies via logistic regression.
    Supplementary reading:
    [BD1] Chap. III, pp. 84–115, Chap. IV, pp. 129–136, Chap. VI, pp. 192–209.
  5. March 21
    Classical methods for analyzing stratified case-control studies with binary exposure. Cochran-Mantel-Haenszel test, Woolf estimator, Mantel-Haenszel estimator.
    Supplementary reading:
    [BD1] Chap. IV, pp. 136–146.
  6. March 28
    Matched case control studies: rationale, implementation of matched design. Choice of matched controls. Analysis of matched case-control studies: Classical methods for estimation and testing of odds ratios in pair-matched studies with binary exposures.
    Supplementary reading:
    [BD1] Chap. V, pp. 162–166.
  7. April 4
    Conditional logistic regression for matched case-control studies. Cohort study.
    Supplementary reading:
    [BD1] Chap VII, pp. 248–253.
  8. April 11
    Survival models for ungrouped cohort data: Cox model, excess relative risk model, additive hazards model. Grouped time-varying exposures, Lexis diagram. Grouped analysis of cohort studies via Poisson regression.
    Supplementary reading:
    [BD2] Chap. 3, pp. 82–91, Chap. 5, pp. 178–197, Chap. 4, pp. 120–150, 159–171.
  9. April 18
    Analysis of Cox model for discrete responses via regression model for binary data with complementary log-log link. Diagnostic methods. Sensitivity, specificity of a diagnostic test. Positive predictive value. ROC curves.
  10. April 25
    Diagnostic tests based on multiple markers. Introduction to clinical trials. Stages of drug development. Clinical trials of Phase I, II, III, and IV.
    Supplementary reading:
    [FFDM] Chap. 1.
  11. May 2
    Clinical trial protocol. Primary and secondary objectives of clinical trial. Outcomes in clinical trials: hard, soft outcomes, surrogate outcomes. Selection of outcome measures. Randomization: simple, blocked, stratified.
    Supplementary reading:
    [FFDM] Chap. 3, pp. 37–51; Chap. 6, pp. 97–105. Example contents of a clinical trial protocol
  12. May 9
    Choice of study population. Inclusion and exclusion criteria. Enrollment of study subjects. Blinding. Interim monotoring, data and safety monitoring board. Analysis set, intent-to-treat principle. Exclusions from analysis set. Principles for choosing appropriate analysis method. Analysis of continuous, binary, time-to-event outcomes in two-arm and multi-arm trials. Analysis of change since baseline.
    Supplementary reading:
    [FFDM] Chap. 4, pp. 55–65; Chap. 5, pp. 79–90; Chap. 7, pp. 119–131; Chap. 10, pp. 183–197.
  13. May 23
    Study design: factorial design, multi-arm design. cross-over trial, non-inferiority trial, group-randomized trial, meta-analysis. Analysis of non-inferiority trials. Interim monitoring of clinical trials. Methods for group-sequential tests. Pocock and O'Brien-Fleming boundaries.
    Supplementary reading:
    [FFDM] Chap. 17, pp. 345–382. [FFDM] Chap. 16, pp. 293–334.

Exercise Class Assignments 

Course Materials 

Course Plan

We will learn statistical methods used in medicine, especially in epidemiology and clinical trials. Terminology specific to medical applications will be explained and some specialized methods will be covered. We will review study designs used in medical studies (cohort study, case-control study, randomized controlled trial) and explain how to analyze each of them. Ethical and administrative aspects of human experiments and their impact on handling statistical issues will be discussed.

Prerequisites

This course assumes advanced knowledge of statistical theory and practice, especially linear regression, logistic regression, loglinear models, survival analysis. Master students of "Probability, statistics and econometrics" must have completed the course on Linear Regression (NMSA407), Advanced Regression Models (NMST432), and Censored Data Analysis (NMST531) before enrolling in this course.