Below is given an overview of the material that have been covered in the course. Section numbers, etc refer to the book by Aalen, Borgan, and Gjessing.
Overview of past lecures
Week 34: Introduction to the course: Section 1.1 (except for examples 1.3, 1.5, 1.6, and 1.7), section 1.2 (except for examples 1.14 and 1.15).
Week 35: Introduction to counting processes: Sections 1.4.1 and 1.4.2. (The students may themselves take a brief look at sections 1.4.3, 1.5.1, and 1.5.2.)
Week 36: Martingales in discrete time: Sections 2.1.1, 2.1.2, and 2.1.3.
Week 37: No lectures.
Week 38: Stochastic processes in continuous time: Introduction to section 2.2, section 2.2.1, section 2.2.2, and section 2.2.5. (The students may themselves take a look at section 2.2.4.) Introduction to the Nelson-Aalen estimator: Introduction to Section 3.1, section 3.1.1 (only to line 14 form above on page 72), section 3.1.5 (only to line 14 from below on page 88).
Week 39: More on stochastic processes in continuous time: Sections 2.2.6 and 2.3.1. The Nelson-Aalen estimator: Sections 3.1.1, 3.1.2, and 3.1.5. (The students should themselves take a look at section 3.1.3.)
Week 40: The martingale central limit theorem: Sections 2.3.2 and 2.3.3. (In section 2.3.3 only conditions (2.60) and (2.61) for the martingale central limit theorem were considered.) Large sample properties of the Nelson-Aalen estimator: Section 3.1.6. Kaplan-Meier estimator: Sections 3.2.1, 3.2.3, and 3.2.4. (The students should themselves take a look at section 3.2.2.)
Week 41: Properties of the Kaplan-Meier estimator: Section 3.2.6. Nonparametric tests: Sections 3.3.1 and 3.3.2. (The students should themselves take a look at sections 3.3.3 and 3.3.4. Those who are interested in the large sample results, should also take a look at section 3.3.5.)
Week 42: Cox regression and relative risk regression models: Introduction to chapter 4, introduction to section 4.1, section 4.1.1 (except examples 4.2 and 4.3).
Week 43: More on relative risk regression models: Section 4.1.2 and section 4.1.5 (only for Cox regression and only for the univariate case, i.e. p=1). The material in section 4.1.5 will not be given at the written exam.
Week 44: Model checking for Cox regression (not given in the ABG-book). Additive regression: Introduction to Section 4.2.
Week 45: Discussion of the trial project .
Week 46: Additive regression: Section 4.2.1 (except the material on smoothing on pp. 159-160), section 4.2.3 (only to line 14 from the top of page 165), and appendices B.1 and B.2. Parametric counting process models: introduction to chapter 5, section 5.1.1, section 5.1.2, and 5.1.3 (only to line 10 from the top of page 211).
Week 47: More on parametric counting process models: Section 5.1.5 (except examples 5.2 and 5.3). Poisson regression: Section 5.2.
Plans for comming lectures
There are no more lectures in the course.