# 447-6236-00L  Statistics for Survival Data

 Semester Frühjahrssemester 2020 Dozierende A. Hauser Periodizität 2-jährlich wiederkehrende Veranstaltung Lehrsprache Englisch

### Lehrveranstaltungen

NummerTitelUmfangDozierende
447-6236-00 VStatistics for Survival Data
Block course
10s Std.
 Mo 08:15-10:00 HG G 19.1 » 13:15-15:00 HG G 19.1 »
A. Hauser
447-6236-00 UStatistics for Survival Data
Block course.
7.5s Std.
 Mo 10:15-12:00 HG G 19.1 » 15:15-17:00 HG G 19.1 »
A. Hauser

### Katalogdaten

 Kurzbeschreibung The primary purpose of a survival analysis is to model and analyze time-to-event data; that is, data that have as a principal endpoint the length of time for an event to occur. This block course introduces the field of survival analysis without getting too embroiled in the theoretical technicalities. Lernziel Presented here are some frequently used parametric models and methods, including accelerated failure time models; and the newer nonparametric procedures which include the Kaplan-Meier estimate of survival and the Cox proportional hazards regression model. The statistical tools treated are applicable to data from medical clinical trials, public health, epidemiology, engineering, economics, psychology, and demography as well. Inhalt The primary purpose of a survival analysis is to model and analyze time-to-event data; that is, data that have as a principal endpoint the length of time for an event to occur. Such events are generally referred to as "failures." Some examples are time until an electrical component fails, time to first recurrence of a tumor (i.e., length of remission) after initial treatment, time to death, time to the learning of a skill, and promotion times for employees.In these examples we can see that it is possible that a "failure" time will not be observed either by deliberate design or due to random censoring. This occurs, for example, if a patient is still alive at the end of a clinical trial period or has moved away. The necessity of obtaining methods of analysis that accommodate censoring is the primary reason for developing specialized models and procedures for failure time data. Survival analysis is the modern name given to the collection of statistical procedures which accommodate time-to-event censored data. Prior to these new procedures, incomplete data were treated as missing data and omitted from the analysis. This resulted in the loss of the partial information obtained and in introducing serious systematic error (bias) in estimated quantities. This, of course, lowers the efficacy of the study. The procedures discussed here avoid bias and are more powerful as they utilize the partial information available on a subject or item.This block course introduces the field of survival analysis without getting too embroiled in the theoretical technicalities. Models for failure times describe either the survivor function or hazard rate and their dependence on explanatory variables. Presented here are some frequently used parametric models and methods, including accelerated failure time models; and the newer nonparametric procedures which include the Kaplan-Meier estimate of survival and the Cox proportional hazards regression model. The statistical tools treated are applicable to data from medical clinical trials, public health, epidemiology, engineering, economics, psychology, and demography as well.

### Leistungskontrolle

 Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) Leistungskontrolle als Semesterkurs ECTS Kreditpunkte 2 KP Prüfende A. Hauser Form unbenotete Semesterleistung Prüfungssprache Englisch Repetition Repetition ohne erneute Belegung der Lerneinheit möglich.

### Lernmaterialien

 Keine öffentlichen Lernmaterialien verfügbar. Es werden nur die öffentlichen Lernmaterialien aufgeführt.

### Gruppen

 Keine Informationen zu Gruppen vorhanden.

### Einschränkungen

 Allgemein : Für Fachstudierende und Hörer/-innen ist eine Spezialbewilligung der Dozierenden notwendig Vorrang Die Belegung der Lerneinheit ist nur durch die primäre Zielgruppe möglich Primäre Zielgruppe Statistik MSc (436000) CAS ETH in Angewandter Statistik (446000) DAS ETH in Angewandter Statistik (447000)

### Angeboten in

StudiengangBereichTyp
CAS in Angewandter StatistikWeitere FächerW
DAS in Angewandter StatistikWahlfächerW
Statistik MasterStatistische und mathematische FächerW