The lectures in STK4900 will take place Monday to Friday during one week in February (16th-20th ) and one week in April (13th-17th)l). The February lectures will be given by Erik B?lviken and the April ones by Bo Lindqvist. The lecture room is Auditorium 1 in the VB-building.
Below is given a preliminary plan for the lectures. Chapters and sections refer to the book by Vittinghoff, Shiboski, Glidden og McCulloch.
Part 1
Monday February 16th:
Explorative and descriptive methods. Basic probability concepts and statistical methods. Sections 2.1-2.3, sections 3.1.1-3.1.3 and 3.1.7, supplementary material. Introduction to R . Slides for Lecture 1.
Tuesday February 17th
One-way ANOVA. Correlation. Simple linear regression. Section 2.4, sections 3.1.4, 3.2, 3.3, supplementary material. Slides for Lecture 2.
Wednesday February 18th:
Multiple linear regression. Section 2.5, sections 4.1, 4.2 (except 4.2.4), 4.3 (except 4.3.4-5). Slides for Lecture 3. Details on the cigarette data are given here
Thursday February 19th:
Confounding. Interaction. More on ANOVA. Sections 4.1, 4.4, and 4.6, supplementary material. Slides for Lecture 4.
Friday February 20th:
Model checking and predictor selection. Section 4.7 and parts of Chapter 5. Slides for Lecture 5.
Part 2
Monday April 13th:
Binary data and proportions. Contingency tables. Risk measures. Introduction to logisitic regression. Sections 3.4 and 5.1, supplementary material. Slides for Lecture 6.
Tuesday April 14th:
Logisitc regression. Maximum likelihood estimation. Deviance and likelihood ratio tests. Sections 5.1, 5.2 (except 5.2.6), and 5.6, supplementary material. Slides for Lecture 7 .
Wednesday April 15th:
Poisson distribution. Poisson regression. Generalized linear models. Chapter 8 (except 8.2), supplementary material. Slide for Lecture 8.
Thursday April 16th:
Survival data and censoring. Kaplan-Meier estimator. Logrank test. Proportional hazards and Cox regression. Sections 3.5, 6.1, and 6.2. Slides for Lecture 9.
Friday April 17th:
Repeated measures and longitudinal data. Sections 7.1-7.5. Slides for Lecture 10.