SubjectsSubjects(version: 849)
Course, academic year 2019/2020
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Censored Data Analysis - NMST531
Title in English: Analýza censorovaných dat
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2017 to 2019
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: English, Czech
Teaching methods: full-time
Additional information:
Guarantor: doc. Mgr. Michal Kulich, Ph.D.
Class: M Mgr. FPM
M Mgr. FPM > Povinně volitelné
M Mgr. PMSE > Povinně volitelné
Classification: Mathematics > Probability and Statistics
Pre-requisite : {Prerekvizita pro NMST531}, NMSA407
Is pre-requisite for: NMST532
Annotation -
Last update: G_M (28.05.2013)
The course connects probability theory (martingales), theoretical statistics (rank tests), reliability theory and survival theory. It will cover counting processes, survival function and hazard function estimates, parametric models, two- and k-sample tests for censored data, regression models. Practice sessions include theoretical exercises and practical applications.
Aim of the course -
Last update: T_KPMS (07.05.2015)

To explain methods for censored data analysis.

Course completion requirements
Last update: RNDr. Jitka Zichová, Dr. (23.04.2018)

The exercise class credit is necessary to sign up for the exam.

Requirements for exercise class credit: The credit for the exercise class will be awarded to the student who is present at the exercise class sessions (two absences are tolerated) and 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.

Literature - Czech
Last update: T_KPMS (16.09.2014)

Fleming TR and Harrington DP "Counting Processes and Survival Analysis" Wiley, New York, 1991.

Kalbfleisch JD and Prentice RL "The Statistical Analysis of Failure Time Data". Wiley, New York, 2002.

Teaching methods -
Last update: T_KPMS (12.05.2014)


Requirements to the exam
Last update: RNDr. Jitka Zichová, Dr. (23.04.2018)

The exam is oral. Requirements for the oral exam comprise the entire extent of the lecture.

Syllabus -
Last update: T_KPMS (16.09.2014)

1. Censored random variable.

2. Parametric models for censored data.

3. Nonparametric estimation of hazard and survival function.

4. Nonparametric two-sample tests.

5. Cox regression model.

6. Transformation models.

7. Diagnostics.

8. Repeated event analysis.

Entry requirements
Last update: doc. Mgr. Michal Kulich, Ph.D. (25.05.2018)

This course assumes the knowledge of linear regression theory and, preferably but not necessarily, generalized linear models. Intermediate-level knowledge of probability theory, including continuous martingales, and counting process theory is also required.

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