1.

Record Nr.

UNINA9910130964503321

Autore

Hosmer David W.

Titolo

Applied survival analysis : regression modeling of time-to-event data / / David W. Hosmer, Stanley Lemeshow, Susanne May / / David W. Hosmer, Stanley Lemeshow, Susanne May

Pubbl/distr/stampa

Hoboken, New Jersey : , : Wiley-Interscience, , 2008

©2008

ISBN

1-283-28250-X

9786613282507

0-470-25801-2

0-470-25800-4

Edizione

[2nd ed.]

Descrizione fisica

1 online resource (418 p.)

Collana

Wiley Series in Probability and Statistics

Disciplina

610.72

610.727

Soggetti

Medicine - Research - Statistical methods

Medical sciences - Statistical methods - Computer programs

Regression analysis - Data processing

Prognosis - Statistical methods

Logistic distribution

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record

Nota di bibliografia

Includes bibliographical references and index

Nota di contenuto

Applied Survival Analysis: Regression Modeling of Time-to-Event Data; Contents; Preface; 1 Introduction to Regression Modeling of Survival Data; 1.1 Introduction; 1.2 Typical Censoring Mechanisms; 1.3 Example Data Sets; Exercises; 2 Descriptive Methods for Survival Data; 2.1 Introduction; 2.2 Estimating the Survival Function; 2.3 Using the Estimated Survival Function; 2.4 Comparison of Survival Functions; 2.5 Other Functions of Survival Time and Their Estimators; Exercises; 3. Regression Models for Survival Data; 3.1 Introduction; 3.2 Semi-Parametric Regression Models

3.3 Fitting the Proportional Hazards Regression Model3.4 Fitting the Proportional Hazards Model with Tied Survival Times; 3.5 Estimating the Survival Function of the Proportional Hazards Regression Model;



Exercises; 4. Interpretation of a Fitted Proportional Hazards Regression Model; 4.1 Introduction; 4.2 Nominal Scale Covariate; 4.3 Continuous Scale Covariate; 4.4 Multiple-Covariate Models; 4.5 Interpreting and Using the Estimated Covariate-Adjusted Survival Function; Exercises; 5. Model Development; 5.1 Introduction; 5.2 Purposeful Selection of Covariates

5.2.1 Methods to examine the scale of continuous covariates in the log hazard5.2.2 An example of purposeful selection of covariates; 5.3 Stepwise, Best-Subsets and Multivariable Fractional PolynomialMethods of Selecting Covariates; 5.3.1 Stepwise selection of covariates; 5.3.2 Best subsets selection of covariates; 5.3.3 Selecting covariates and checking their scale using multivariable fractional polynomials; 5.4 Numerical Problems; Exercises; 6. Assessment of Model Adequacy; 6.1 Introduction; 6.2 Residuals; 6.3 Assessing the Proportional Hazards Assumption

6.4 Identification of Influential and Poorly Fit Subjects6.5 Assessing Overall Goodness-of-Fit; 6.6 Interpreting and Presenting Results From the Final Model; Exercises; 7. Extensions of the Proportional Hazards Model; 7.1 Introduction; 7.2 The Stratified Proportional Hazards Model; 7.3 Time-Varying Covariates; 7.4 Truncated, Left Censored and Interval Censored Data; Exercises; 8. Parametric Regression Models; 8.1 Introduction; 8.2 The Exponential Regression Model; 8.3 The Weibull Regression Model; 8.4 The Log-Logistic Regression Model; 8.5 Other Parametric Regression Models; Exercises

9. Other Models and Topics9.1 Introduction; 9.2 Recurrent Event Models; 9.3 Frailty Models; 9.4 Nested Case-Control Studies; 9.5 Additive Models; 9.6 Competing Risk Models; 9.7 Sample Size and Power; 9.8 Missing Data; Exercises; Appendix 1 The Delta Method; Appendix 2 An Introduction to the Counting Process Approach to Survival Analysis; Appendix 3 Percentiles for Computation of the Hall and Wellner Confidence Band; References; Index

Sommario/riassunto

THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA-NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edi