Mario Cleves:Introduction to Survival Analysis Using Stata, Revised Third Edition (Paperback)
- Taschenbuch 2016, ISBN: 1597181749
[EAN: 9781597181747], Neubuch, [PU: Stata Press, College Station], Paperback. An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professiona… Mehr…
[EAN: 9781597181747], Neubuch, [PU: Stata Press, College Station], Paperback. 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 versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata's survival analysis routines. The 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. Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement, Stata provides the st family of commands for organizing and summarizing survival data. This book provides statistical theory, step-by-step procedures for analyzing survival data, an in-depth usage guide for Stata's most widely used st commands, and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata. The first three chapters of the text cover basic theoretical concepts: hazard functions, cumulative hazard functions, and their interpretations; survivor functions; hazard models; and a comparison of nonparametric, semiparametric, and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting, manipulation, stsetting, and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods, including the Kaplan-Meier and Nelson-Aalen estimators and the various nonparametric tests for the equality of survival experience. Chapters 9-11 discuss Cox regression and include various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, model diagnostics, and regression with survey data. The next four chapters cover parametric models, which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate, as well as information on stratification, obtaining predictions, and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks. Revison of: Maximum likelihood estimation with Stata / William Gould, Jeffrey Pitblado, William Sribney. c2006. 3rd ed. Shipping may be from multiple locations in the US or from the UK, depending on stock availability., Books<
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An Introduction to Survival Analysis Using Stata, Revised Third Edition Mario Cleves Author
- neues BuchISBN: 9781597181747
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 … Mehr…
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 versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata’s survival analysis routines. The 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. Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement, Stata provides the st family of commands for organizing and summarizing survival data. This book provides statistical theory, step-by-step procedures for analyzing survival data, an in-depth usage guide for Stata's most widely used st commands, and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata. The first three chapters of the text cover basic theoretical concepts: hazard functions, cumulative hazard functions, and their interpretations; survivor functions; hazard models; and a comparison of nonparametric, semiparametric, and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting, manipulation, stsetting, and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods, including the Kaplan–Meier and Nelson–Aalen estimators and the various nonparametric tests for the equality of survival experience. Chapters 9–11 discuss Cox regression and include various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, model diagnostics, and regression with survey data. The next four chapters cover parametric models, which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate, as well as information on stratification, obtaining predictions, and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks. New Textbooks>Trade Paperback>Science>Statistics & Probability>Statistics & Probability, Taylor & Francis Core >1 >T<
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Mario Cleves:An Introduction to Survival Analysis Using Stata, Revised Third Edition
- Taschenbuch 2016, ISBN: 1597181749
[EAN: 9781597181747], Neubuch, [PU: Stata Press Mai 2016], MATHEMATICS; MATHEMATICS / PROBABILITY & STATISTICS GENERAL, Neuware - An Introduction to Survival Analysis Using Stata, Revised… Mehr…
[EAN: 9781597181747], Neubuch, [PU: Stata Press Mai 2016], MATHEMATICS; MATHEMATICS / PROBABILITY & STATISTICS GENERAL, Neuware - 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 versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata's survival analysis routines.The 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.Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement, Stata provides the st family of commands for organizing and summarizing survival data.This book provides statistical theory, step-by-step procedures for analyzing survival data, an in-depth usage guide for Stata's most widely used st commands, and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata.The first three chapters of the text cover basic theoretical concepts: hazard functions, cumulative hazard functions, and their interpretations; survivor functions; hazard models; and a comparison of nonparametric, semiparametric, and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting, manipulation, stsetting, and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods, including the Kaplan-Meier and Nelson-Aalen estimators and the various nonparametric tests for the equality of survival experience.Chapters 9-11 discuss Cox regression and include various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, model diagnostics, and regression with survey data. The next four chapters cover parametric models, which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate, as well as information on stratification, obtaining predictions, and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks., Books<
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An Introduction to Survival Analysis Using Stata Revised Third Edition
- neues BuchISBN: 9781597181747
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 … Mehr…
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 versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Statas survival analysis routines. The 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. Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement Stata provides the st family of commands for organizing and summarizing survival data. This book provides statistical theory step-by-step procedures for analyzing survival data an in-depth usage guide for Stata's most widely used st commands and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata. The first three chapters of the text cover basic theoretical concepts: hazard functions cumulative hazard functions and their interpretations; survivor functions; hazard models; and a comparison of nonparametric semiparametric and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting manipulation stsetting and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods including the KaplanMeier and NelsonAalen estimators and the various nonparametric tests for the equality of survival experience. Chapters 911 discuss Cox regression and include various examples of fitting a Cox model obtaining predictions interpreting results building models model diagnostics and regression with survey data. The next four chapters cover parametric models which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate as well as information on stratification obtaining predictions and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks. Media > Books > Print Books new, Stata Press<
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Mario Cleves; William Gould; Yulia Marchenko:Introduction to Survival Analysis Using Stata
- Taschenbuch 2016, ISBN: 9781597181747
Buch, Softcover, 3rd Revised edition, [PU: Stata Press], Stata Press, 2016
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