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Produktbild: An Introduction to Survival Analysis Using Stata, Revised Third Edition

An Introduction to Survival Analysis Using Stata, Revised Third Edition

Fr. 129.00

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

10.05.2016

Verlag

Taylor & Francis

Seitenzahl

428

Maße (L/B/H)

23.3/18.2/3 cm

Gewicht

913 g

Auflage

4th edition

Sprache

Englisch

ISBN

978-1-59718-174-7

Beschreibung

Rezension

"This is an application-oriented introduction to survival analysis using Stata. The authors have focused on intuitions without getting into technical details. For example ... the rather mysterious partial likelihood was elegantly illustrated with a small dataset and simple derivations for conditional probabilities. The book provides an excellent coverage of commonly used nonparametric, semiparametric, and parametric analyses of survival data, with ample application examples. The implementation of each survival approach has been carefully laid out in Stata syntax and real data analyses. Moreover, the material covered in the book is surprisingly comprehensive, including Coxmodels with time-varying covariates, shared frailty models, multiple imputations, and competing risk regression. Those topics are often encountered in practice but usually missing from an introductory book of survival analysis. The revised third edition has been updated to reflect the welcome additions in Stata 14 relative to previous versions. ... The revised third edition provides not only an excellent tutorial to anyone who is interested in learning survival models with examples, but also an extremely handy reference to researchers who would like to perform survival analyses in Stata."
-Yu Cheng, University of Pittsburgh, in The American Statistician, April 2018

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

10.05.2016

Verlag

Taylor & Francis

Seitenzahl

428

Maße (L/B/H)

23.3/18.2/3 cm

Gewicht

913 g

Auflage

4th edition

Sprache

Englisch

ISBN

978-1-59718-174-7

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: An Introduction to Survival Analysis Using Stata, Revised Third Edition
  • The problem of survival analysis Parametric modeling Semiparametric modelingNonparametric analysis Linking the three approaches Describing the distribution of failure times The survivor and hazard functionsThe quantile functionInterpreting the cumulative hazard and hazard rate Means and medians Hazard models Parametric modelsSemiparametric modelsAnalysis time (time at risk) Censoring and truncation Censoring Truncation Recording survival data The desired format Other formatsExample: Wide-form snapshot data Using stset A short lesson on datesPurposes of the stset commandSyntax of the stset command After stset Look at stset’s outputList some of your data Use stdescribeUse stvary Perhaps use stfill Example: Hip-fracture data Nonparametric analysis Inadequacies of standard univariate methods The Kaplan–Meier estimator The Nelson–Aalen estimatorEstimating the hazard functionEstimating mean and median survival timesTests of hypothesis The Cox proportional hazards model Using stcox Likelihood calculations Stratified analysis Cox models with shared frailty Cox models with survey data Cox model with missing data—multiple imputation Model building using stcox Indicator variablesCategorical variablesContinuous variables InteractionsTime-varying variables Modeling group effects: fixed-effects, random-effects, stratification, and clustering The Cox model: Diagnostics Testing the proportional-hazards assumption Residuals and diagnostic measures Reye’s syndrome data Parametric models MotivationClasses of parametric models A survey of parametric regression models in Stata The exponential model Weibull regression Gompertz regression (PH metric)Lognormal regression (AFT metric)Loglogistic regression (AFT metric)Generalized gamma regression (AFT metric)Choosing among parametric models Postestimation commands for parametric models Use of predict after streg Using stcurvePredictive margins and marginal effects Generalizing the parametric regression model 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 Competing risks Cause-specific hazardsCumulative incidence functionsNonparametric analysis Semiparametric analysis Parametric analysis