Notifications
Exam opportunities can be arranged throughout the summer upon email request.
Schedule
Lectures  
Tuesday  15:40  17:10  K7  
Exercise Class  
Monday  17:20  18:50  K4  (Instructor: Martin Otava) 
Course Materials
 Course notes (last updated May 26, 2021)
 Slides on clinical trials, part 1
 Slides on clinical trials, part 2
 Slides on clinical trials, part 3
 Clinical trial protocol contents (example)
 Example clinical trial protocol is available in the SIS module Předměty (only for students enrolled in the course, requires login)
 Presentation on data sampling mechanisms
Progress of lectures

Tuesday Feb. 14.
Introduction. Basic
epidemiologic terms. Left truncated data. Empirical incidence
estimates.
Course notes, Sec. 1.11.4, pp. 610.
Supplementary reading: Esteve, Benhamou, Raymond (Chap. 1, pp. 115).

Tuesday Feb. 21.
Agespecific
incidence, agestandardized incidence, cumulative incidence.
Exposuredisease associations: Excess risk, relative risk.
Course notes, Sec. 1.41.6, pp. 1115.
Supplementary reading: Esteve, Benhamou, Raymond (Chap. 2, pp. 4962). BD1 (Sec. 2.12.4, pp. 4259).

Tuesday Feb. 28.
Exposuredisease
associations. Introduction to epidemiological study design. Odds ratio
estimation and testing.
Course notes, Sec. 1.62.1, pp. 1621.
Supplementary reading: BD1 (Sec. 2.8, pp. 6973, Sec. 4.3, pp. 129136).

Tuesday March 7.
Exact inference on
odds ratio via conditional likelihood. Confounding in
epidemiological studies.
Course notes, Sec. 2.22.5, pp. 2126.
Supplementary reading: BD1, (Sec. 4.2, pp. 124129, Sec. 3.13.4, pp. 8599).

Tuesday March 14.
Sources of bias in
epidemiological studies. Presentation on confounding in flu vaccine studies.
Course notes, Sec. 2.5, pp. 2628.
Supplementary reading: BD1, (Sec. 3.4, pp. 103115).

Tuesday March 21.
Analysis of
stratified casecontrol studies: classical methods.
Course notes, Sec. 3.13.2, pp. 2933.
Supplementary reading: BD1, (Sec. 4.4, pp. 136146).

Tuesday March 28.
Logistic regression for
stratified casecontrol studies. Analysis of
matched casecontrol studies: classical methods.
Course notes, Sec. 3.3, 4.1, 4.2, pp. 3340.
Supplementary reading: BD1, (Sec. 6.16.5, pp. 193213, Sec. 5.2, pp. 164166).

Tuesday Apr. 4.
Conditional
logistic regression for matched casecontrol studies.
Course notes, Sec. 4.3, pp. 4144.
Supplementary reading: BD1, (Sec. 7.17.4, pp. 248268).

Tuesday Apr. 11.
Analysis of
cohort studies: ungrouped and grouped data. Discrete Cox model.
Course notes, Sec. 5.15.4, pp. 4553.
Supplementary reading: BD2, (Chap. 5, pp. 178197, Chap. 3, pp. 82–91, Chap. 4, pp. 120–171).

Tuesday Apr. 18.
Discrete Cox
model. Diagnostic tests.
Course notes, Sec. 5.4, 6.1–6.4 pp. 5363.

Tuesday Apr. 25.
Drug development
process. Phases of clinical trials.
Supplementary reading: FFD (Chap. 1, pp. 114).

Tuesday May 2.
Phase III trials:
protocol, objectives, endpoints, population, randomization, blinding.
Supplementary reading: FFD (Chap. 3, pp. 3751, Chap. 4, pp. 5565, Chap. 6, pp. 97105, Chap. 7, pp. 119131).
Textbooks
 [EBR] Esteve J, Benhamou E, Raymond L. Statistical Methods in Cancer Research, Vol. IV: Descriptive Epidemiology. International Agency for Research on Cancer: Lyon, 1994.
 [BD1] Breslow NE, Day NE. Statistical Methods in Cancer Research, Vol. I: The analysis of casecontrol studies. International Agency for Research on Cancer: Lyon, 1980.
 [BD2] Breslow NE, Day NE. Statistical Methods in Cancer Research, Vol. II: The design and analysis of cohort studies. International Agency for Research on Cancer: Lyon, 1987.
 [FFD] Friedman LM, Furberg CD, DeMets DL. Fundamentals of Clinical Trials. 4th Ed., Springer: New York, 2010.
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, casecontrol 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.