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Written by the developers of Stata's widely used survival analysis suite, this book provides the foundation to understand various approaches for analyzing time-to-event data. Taking a practical approach to the subject, the authors discuss how survival analysis estimators work and what information they exploit. They also present the syntax, features, and underpinnings of Stata's survival analysis routines. This edition highlights the new aspects of Stata 10, including its power and sample-size calculations for survival data. Other updates include in-graph at-risk tables for Kaplan--Meier and related curves, survival analysis for survey data, and regression models with flexible functional forms via fractional polynomials.
| ISBN | 1597180416 | | Pages | 372 | | ISBN13 | 9781597180412
(What's this?) | | Volumes | 001 | | Publisher | Stata Press | | Weight (grammes) | 794 | | Imprint | Stata Press | | Published in | College Station | | Format | Paperback | | Previous ISBN | 9781881228844 | | Publication date | 15 May 2008 | | Height (mm) | 235 | | Library of Congress | QA276.4 | | Width (mm) | 187 | | DEWEY | 005.55 | | Spine width (mm) | 25 | | DEWEY edition | DC21 | | Academic level | Professional / Scholarly |
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The Problem of Survival Analysis Parametric modeling Semiparametric modeling Nonparametric analysis Linking the three approaches Describing the Distribution of Failure Times The survivor and hazard functions The quantile function Interpreting the cumulative hazard and hazard rate Means and medians Hazard Models Parametric models Semiparametric models Analysis time (time at risk) Censoring and Truncation Censoring Truncation Recording Survival Data The desired format Other formats Example: wide-form snapshot data Using stset A short lesson on dates Purposes of the stset command Syntax of the stset command After stset Look at stset's output List some of your data Use stdescribe Use stvary Perhaps use stfill Example: hip fracture data Nonparametric Analysis Inadequacies of standard univariate methods The Kaplan--Meier estimator The Nelson--Aalen estimator Estimating the hazard function Estimating mean and median survival times Tests of hypothesis The Cox Proportional Hazards Model Using stcox Likelihood calculations Stratified analysis Cox models with shared frailty Cox models with survey data Model Building Using stcox Indicator variables Categorical variables Continuous variables Interactions Time-varying variables Modeling group effects: fixed-effects, random-effects, stratification, and clustering The Cox Model: Diagnostics Testing the proportional-hazards assumption Residuals Parametric Models Motivation Classes of parametric models A Survey of Parametric Regression Models in Stata The exponential model Weibull regression Gompertz regression (PHmetric) Lognormal regression (AFTmetric) Loglogistic regression (AFTmetric) Generalized gamma regression (AFTmetric) Choosing among parametric models Postestimation Commands for Parametric Models Use of predict after streg Using stcurve Generalizing the Parametric Regression Model Using the ancillary() option Stratified models Frailty models Power and Sample-Size Determination for Survival Analysis Estimating sample size Accounting for withdrawal and accrual of subjects Estimating power and effect size Tabulating or graphing results References Author Index Subject Index
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