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An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professional data analysts who want to learn survival analysis for the first time or who are well versedin survival analysis but are not as dexterous in using Stata toanalyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata's survival analysis routines.
This revised third edition has been updated for Stata 14, and it includes a new section on predictive margins and marginal effects, which demonstrates how to obtain and visualize marginal predictions and marginal effects using the margins and marginsplot commands after survival regression models.
An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professional data analysts who want to learn survival analysis for the first time or who are well versedin survival analysis but are not as dexterous in using Stata toanalyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata's survival analysis routines.
This revised third edition has been updated for Stata 14, and it includes a new section on predictive margins and marginal effects, which demonstrates how to obtain and visualize marginal predictions and marginal effects using the margins and marginsplot commands after survival regression models.
Mario Cleves is Professor and the Biostatistics Section Chief in the Department of Pediatrics at the University of Arkansas for Medical Sciences.
William Gould is the president and head of development at StataCorp.
Yulia Marchenko is a senior statistician at StataCorp.
All are authors of Stata statistical software, in particular, Stata's widely used survival analysis suite.
The problem of survival analysis. Describing the distribution of failure times. Hazard models. Censoring and truncation. Recording survival data. Using stset. After stet. Nonparametric analysis. Using stcox. Model building using stcox. The Cox model: Diagnostics. Parametric models. The exponential model. Postestimation commands for parametric models. Generalizing the parametric regression model. Power and sample-size determination for survival analysis. Competing risks.
Mario Cleves is Professor and the Biostatistics Section Chief in the Department of Pediatrics at the University of Arkansas for Medical Sciences.
William Gould is the president and head of development at StataCorp.
Yulia Marchenko is a senior statistician at StataCorp.
All are authors of Stata statistical software, in particular, Stata's widely used survival analysis suite.
The problem of survival analysis. Describing the distribution of failure times. Hazard models. Censoring and truncation. Recording survival data. Using stset. After stet. Nonparametric analysis. Using stcox. Model building using stcox. The Cox model: Diagnostics. Parametric models. The exponential model. Postestimation commands for parametric models. Generalizing the parametric regression model. Power and sample-size determination for survival analysis. Competing risks.
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