Schedule 

Lectures
Tuesday 14:00 - 15:30 K7  
Exercise Class
Tuesday 17:20 - 18:50 K6 (Instructor: Martin Otava)

Course Materials 

Progress of lectures

  1. Friday Feb. 23. Introduction. Basic epidemiologic terms. Left truncated data. Empirical incidence estimates.

    Course notes, Sec. 1.1-1.4, pp. 6-10.

    Supplementary reading: Esteve, Benhamou, Raymond (Chap. 1, pp. 1-15).

  2. Friday Mar. 1. Age-specific incidence, age-standardized incidence, cumulative incidence. Exposure-disease associations: Excess risk, relative risk.

    Course notes, Sec. 1.4-1.6, pp. 11-14.

    Supplementary reading: Esteve, Benhamou, Raymond (Chap. 2, pp. 49-62). BD1 (Sec. 2.1-2.4, pp. 42-59).

  3. Tuesday Mar. 5. Exposure-disease associations. Introduction to epidemiological study design. Odds ratio estimation and testing.

    Course notes, Sec. 1.6-2.1, pp. 15-20.

    Supplementary reading: BD1 (Sec. 2.8, pp. 69-73, Sec. 4.3, pp. 129-136).

  4. Tuesday Mar. 12. Exact inference on odds ratio via conditional likelihood. Confounding in epidemiological studies.

    Course notes, Sec. 2.2-2.5, pp. 20-26.

    Supplementary reading: BD1, (Sec. 4.2, pp. 124-129, Sec. 3.1-3.4, pp. 85-99).

  5. Tuesday March 19. Sources of bias in epidemiological studies.

    Course notes, Sec. 2.5, pp. 26-28.

    Supplementary reading: BD1, (Sec. 3.4, pp. 103-115).

  6. Tuesday March 26. Analysis of stratified case-control studies: classical methods.

    Course notes, Sec. 3.1-3.2, pp. 29-33.

    Supplementary reading: BD1, (Sec. 4.4, pp. 136-146).

Textbooks 

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.