NMST511 - Censored Data Analysis (Exercise class)
SIS page : NMST511
Schedule : on Thursday 14:00 - 15:30 in classroom K5 (your own laptops are needed, the room is not equipped)
Language : materials in English, instructed in Czech (unless anybody requires English)
Instructor e-mail : vavraj@karlin.mff.cuni.cz (for sending solutions to assignments)
Lecture web page (from previous years): www.karlin.mff.cuni.cz/~kulich/vyuka/cens/index.html
Note : exercises will start in November since many scheduled classes will become lectures (with doc. Hlubinka) at the beggining of the term
Credit
- Satisfactory solution to given assignments by the prescribed deadline.
(If your solution will not be satisfactory enough, you might be asked for revision.)
Send your solutions via email to address vavraj@karlin.mff.cuni.cz.
Recommended form: Rmarkdown output (preferably PDF to HTML)
Overview
Exercise 1 (7-14th November)
- Topic: Parametric regression models for censored data
- Dataset:
pbc
dataset fromlibrary(survival)
- Assignment: Find suitable model for survival time and interpret it.
- Deadline: Monday 14th November 9:00
Exercise 2 (14-21st November)
- Topic: Non-parametric estimation of cumulative hazard and survival function
- Dataset: fans
- Assignment: Calculate and plot [NA], [KM], [FH]
estimates both manually and using
survfit
function fromlibrary(survival)
. - Deadline: Monday 21st November 9:00
Exercise 3 (21-28th November)
- Topic: Actuarial (lifetable) estimator of the survival
- Dataset: nurshome,
mort.m
andmort.f
from mort.RData - Assignment: Compare non-grouped and grouped
approaches for estimation survival and hazard function for two
subpopulations in
nurshome
dataset. Compare survival estimators with the output from ČSÚ: males and females. - Deadline: Monday 28th November 9:00
Exercise 4 (28th November - 5th December)
- Topic: Confidence intervals and bands for survival function
- Dataset: km_all.RData
- Assignment: Compute and plot [KM] estimates including Hall-Werner bands. Perform short (or long if you wish) simulation study.
- Deadline: Monday 5th December 9:00
Exercise 5 (5-13th December)
- Topic: Testing equality of censored distributions
- Datasets: km_all.RData
- Assignment: Calculate and plot [KM], [NA] estimates and smoothed estimator of hazard function when differentiating different groups. Perform two-sample tests and decide (based on the plots) which test statistic would be the most appropriate.
- Deadline: Tuesday 13th December 9:00 (also for Ex 6!)
Exercise 6 (5-13th December)
- HELD TOGETHER WITH Ex5 on 5th December at 12:20!
- Topic: The choice of two-sample test statistic
- Datasets:
data(veteran)
, nurshome - Assignment: Fill table of appropriateness of different weights in two-sample survival tests in different situations. Perform several real data analyses and simulation study.
- Deadline: Tuesday 13th December 9:00 (also for Ex 5!)
Exercise 7 (13th December - 2nd January)
- Held on Tuesday 13th December at 14:00!!! On Monday 12th December there will be a lecture on Cox model by doc. Hlubinka.
- Topic: Building Cox models for censored data (constant covariates)
- Dataset:
pbc
dataset fromlibrary(survival)
- Assignment: Perform exploratory analysis focused on the influence of covariates on the survival probability. Build a reasonable Cox model (starting from simple univariate models). Compare your final Cox model to your final model from Exercise 1.
- Deadline: Monday 2nd January 9:00
Bonus Exercise (not scheduled)
- Topic: Generalizations of the Cox model
- Dataset:
pbc
andcgd
datasets fromlibrary(survival)
- Assignment: None, just admire what else could be done with the Cox model.
Exercise 8 (2-9th January)
- Topic: Time-varying covariates in the Cox model
- Dataset:
jasa
andheart
dataset fromlibrary(survival)
- Assignment: Try to reproduce
heart
dataset fromjasa
. Build and interpret Cox model with covariate indicating the time of heart transplantation and other fixed covariates. Does transplantation help patients to survive longer? Plot estimated survival functions. - Deadline: Monday 16th January 9:00