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 Reference: Garson, G. D. (2012). Life Tables and Kaplan-Meier Analysis. Asheboro, NC: Statistical Associates Publishers. Instant availablity without passwords in Kindle format on Amazon: Not yet available. Tutorial on the free Kindle for PC Reader app: click here. Obtain the free Kindle Reader app for any device: click here. Delayed availability with passwords in free pdf format: right-click here and save file. Register to obtain a password: click here. Statistical Associates Publishers home page. About the author Overview Table of Contents ASIN number (e-book counterpart to ISBN): B00B0N2S7E @c 2012 by G. David Garson and Statistical Associates Publishers. worldwide rights reserved in all languages and on all media. Permission is not granted to copy, distribute, or post e-books or passwords.

LIFE TABLES & KAPLAN-MEIER ANALYSIS: NONPARAMETRIC SURVIVAL ANALYSIS

Overview

Life tables refers to a statistical procedure which generates duration (time to event) distributions for an entire dataset or separately for each level of a factor. As such it is a form of nonparametric survival analysis. The primary output is a life table in which the rows are researcher-defined time intervals and the columns have to do with counts, probabilities, and cumulative probabilities of the event of interest occurring during the given time interval.

Kaplan-Meier survival analysis (KMSA) is a method of generating tables and plots of survival or hazard functions for event history data (time to event data). Time to event data might include time to a report of symptomatic relief following a treatment or time to making a contribution following receipt of a fund-raising appeal. KMSA is also a form of nonparametric survival analysis. That is, KMSA is a descriptive procedure for time-to-event variables for use when time is considered the only salient variable.

Life tables and KMSA are not preferred when the purpose is to investigate the effects of covariates on time to event. Rather, parametric survival analysis methods or Cox regression (both discussed in separate volumes of the Statistical Associates "Blue Book" series) are typically used. If covariates other than time are thought to be important in determining duration to outcome, results reported by KMSA will represent misleading averages, obscuring important differences in groups formed by the covariates (ex., men vs. women). However, even when covariates may be found to be important, KMSA may still be fruitful in exploratory stages of research.

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Below is the unformatted table of contents.

```LIFE TABLES AND KAPLAN-MEIER ANALYSIS
Table of Contents
Overview	5
Life Tables	6
Key Terms and Concepts	6
Example	6
Variables	6
Life tables analysis in SPSS	7
The SPSS user interface	7
SPSS options	8
SPSS life tables output	9
The life table	9
Median survival time table	10
Overall comparisons table	10
Survival function plot	12
One minus survival plot	13
Density function plot	14
Hazard function plot	14
Assumptions of life tables analysis	15
Censored cases not different	15
Probabilities depend on time	15
Kaplan-Meier Analysis	15
Overview	15
Key Concepts and Terms	16
Example	16
Censored cases	16
Time variable	17
Status variable	18
Stratification variable	18
Factors and factor comparisons	18
The “Compare Factor” button	19
The overall comparisons table	19
Survival tables and plots	21
Survival table	21
Mean and median for survival time table	22
The quartiles/percentiles table	23
The survival plot	23
The “One minus survival functions” plot	24
Hazard plot	25
Log survival plot	26
Saving output as variables	27
Assumptions	28
Events dependent only on time	28
Frequently asked questions about KMSA	29
How do you obtain KMSA output in Stata?	29
How are Kaplan-Meier survival tables related to "Life Tables"?	30
Bibliography	30
Pagecount: 32
```