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Applied Survival Analysis : Regression Modeling of Time to Event Data.

Author: David W Hosmer; Stanley Lemeshow; Susanne May
Publisher: Hoboken : Wiley, 2011.
Series: Wiley series in probability and statistics.
Edition/Format:   eBook : Document : English : 2nd edView all editions and formats
Database:WorldCat
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Hosmer, David W.
Applied Survival Analysis : Regression Modeling of Time to Event Data.
Hoboken : Wiley, ©2011
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: David W Hosmer; Stanley Lemeshow; Susanne May
ISBN: 9780470258002 0470258004
OCLC Number: 794326228
Description: 1 online resource (418 pages).
Contents: 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.
Series Title: Wiley series in probability and statistics.

Abstract:

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.

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