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Censored Data Analysis (NMST511), exercise class

Winter semester 2024–25

SIS pages of the course:

ENG

CZE

TIMETABLE

Lectures:	Thursday 11:30 in K3	(doc. RNDr. Daniel Hlubinka, Ph.D.)
Exercise class:	Monday 17:20 in K10C

ANNOUNCEMENTS

In the first few weeks of semester the slot of the exercise class will be used for the lecture as well.

EXERCISE CLASS MATERIALS

Exercise 1 (11/11/2024)

Topic: Parametric regression models for censored data

Dataset:	pbc dataset from the R package survival
Assignment:	Find a suitable model for the survival time and interpret it.

Exercise 2 (18/11/2024)

Topic: Non-parametric estimation of cumulative hazard and survival function

Dataset:	fans
Assignment:	Calculate and plot [NA], [KM], [FH] estimates, both manually and using the survfit function from the survivalpackage.

Exercise 3 (optional)

Topic: Actuarial (lifetable) estimator of the survival

Dataset 1:	NursingHome
Dataset 2:	mort2022
Dataset 3:	umrtnost_cr_m_2022
Dataset 4:	umrtnost_cr_z_2022
Assignment:	Actuarial (lifetable) estimators of the survival.

Exercise 4 (25/11/2024)

Topic: Confidence intervals and bands for the survival function

Dataset:	km_all
Assignment:	Confidence intervals and bands for the survival function.

Exercise 5 (02/12/2024)

Topic: Testing equality of survival distributions and choice of the two-sample test statistic

Dataset:	km_all
Assignment:	Two-sample comparisons.

Exercise 6 (09/12/2024)

Topic: Building the Cox model (time-constant covariates)

Dataset:	pbc dataset from the R package survival
Assignment:	Proportional hazard models.

Exercise 7 (19/12/2023)

Topic: Time-varying covariates in the Cox model

Dataset:

jasa and heart datasets from the R package survival

REQUIREMENTS TO GET A COURSE CREDIT (ZÁPOČET)

The course credit for the exercise class will be awarded to the student who hands in a satisfactory solution to each assignment by the prescribed deadline. The nature of these requirements precludes any possibility of additional attempts to obtain the exercise class credit.