Event History Analysis with R

by Brostr÷m; G÷ran

• ISBN13: 9781439831649
• ISBN10: 1439831645
• Edition: 1st
• Format: Hardcover
• Copyright: 2012-04-03
• Publisher: CRC Press

Summary

With an emphasis on social science applications, this book presents an introduction to survival and event history analysis. It focuses on practical applications in the fields of demography, epidemiology, and econometrics. The text includes a wide range of real examples, with data available online and supported by a dedicated R package for performing all of the analyses. Keeping mathematical details to a minimum, the author covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. He also describes how to use methods that are not available in other software for survival analysis.

Table of Contents

List of Figures	p. ix
List of Tables	p. xiii
Preface	p. xv
Event History and Survival Data	p. 1
Introduction	p. 1
Survival Data	p. 1
Right Censoring	p. 5
Left Truncation	p. 6
Time Scales	p. 7
Event History Data	p. 9
More Data Sets	p. 11
Single Sample Data	p. 17
Introduction	p. 17
Continuous Time Model Descriptions	p. 17
Discrete Time Models	p. 22
Nonparametric Estimators	p. 23
Doing it in R	p. 27
Cox Regression	p. 31
Introduction	p. 31
Proportional Hazards	p. 31
The Log-Rank Test	p. 33
Proportional Hazards in Continuous Time	p. 39
Estimation of the Baseline Hazard	p. 42
Explanatory Variables	p. 42
Interactions	p. 44
Interpretation of Parameter Estimates	p. 47
Proportional Hazards in Discrete Time	p. 47
Model Selection	p. 48
Male Mortality	p. 49
Poisson Regression	p. 57
Introduction	p. 57
The Poisson Distribution	p. 57
The Connection to Cox Regression	p. 59
The Connection to the Piecewise Constant Hazards Model	p. 62
Tabular Lifetime Data	p. 62
More on Cox Regression	p. 677
Introduction	p. 67
Time-Varying Covariates	p. 67
Communal covariates	p. 68
Tied Event Times	p. 71
Stratification	p. 74
Sampling of Risk Sets	p. 75
Residuals	p. 77
Checking Model Assumptions	p. 80
Fixed Study Period Survival	p. 83
Left- or Right-Censored Data	p. 84
Parametric Models	p. 85
Introduction	p. 85
Proportional Hazards Models	p. 85
Accelerated Failure Time Models	p. 112
Proportional Hazards or AFT Model?	p. 115
Discrete Time Models	p. 116
Multivariate Survival Models	p. 127
Introduction	p. 127
Frailty Models	p. 129
Parametric Frailty Models	p. 134
Stratification	p. 136
Competing Risks Models	p. 139
Introduction	p. 139
Some Mathematics	p. 140
Estimation	p. 140
Meaningful Probabilities	p. 140
Regression	p. 141
R Code for Competing Risks	p. 144
Causality and Matching	p. 147
Introduction	p. 147
Philosophical Aspects of Causality	p. 147
Causal Inference	p. 148
Aalen's Additive Hazards Model	p. 150
Dynamic Path Analysis	p. 152
Matching	p. 153
Conclusion	p. 157
Basic Statistical Concepts	p. 159
Introduction	p. 159
Statistical Inference	p. 159
Asymptotic theory	p. 161
Model Selection	p. 163
Survival Distributions	p. 165
Introduction	p. 165
Relevant Distributions in R	p. 165
Parametric Proportional Hazards and Accelerated Failure Time Models	p. 172
A Brief Introduction to R	p. 177
R in General	p. 177
Some Standard R Functions	p. 182
Writing Functions	p. 187
Graphics	p. 193
Probability Functions	p. 194
Help in R	p. 197
Functions in eha and survival	p. 197
Reading Data into R	p. 202
Survival Packages in R	p. 205
Introduction	p. 205
eha	p. 205
survival	p. 206
Other Packages	p. 207
Bibliography	p. 209
Index	p. 213
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