Applied Survival Analysis / Wiley Series in Probability and Statistics (ePub)
Regression Modeling of Time-to-Event Data
(Sprache: Englisch)
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...
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...
sofort als Download lieferbar
eBook (ePub)
Fr. 135.00
inkl. MwSt.
- Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Applied Survival Analysis / Wiley Series in Probability and Statistics (ePub)“
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 Edition provides a comprehensive
and up-to-date introduction to regression modeling for
time-to-event data in medical, epidemiological, biostatistical, and
other health-related research.
This book places a unique emphasis on the practical and
contemporary applications of regression modeling rather than the
mathematical theory. It offers a clear and accessible presentation
of modern modeling techniques supplemented with real-world examples
and case studies. Key topics covered include: variable selection,
identification of the scale of continuous covariates, the role of
interactions in the model, assessment of fit and model assumptions,
regression diagnostics, recurrent event models, frailty models,
additive models, competing risk models, and missing data.
Features of the Second Edition include:
* Expanded coverage of interactions and the covariate-adjusted
survival functions
* The use of the Worchester Heart Attack Study as the main
modeling data set for illustrating discussed concepts and
techniques
* New discussion of variable selection with multivariable
fractional polynomials
* Further exploration of time-varying covariates, complex with
examples
* Additional treatment of the exponential, Weibull, and
log-logistic parametric regression models
* Increased emphasis on interpreting and using results as well as
utilizing multiple imputation methods to analyze data with missing
values
* New examples and exercises at the end of each chapter
Analyses throughout the text are performed using Stata®
Version 9, and an accompanying FTP site contains the data sets used
in the book. Applied Survival Analysis, Second Edition is an ideal
book for graduate-level courses in biostatistics, statistics, and
epidemiologic methods. It also serves as a valuable reference for
practitioners and researchers in any health-related field or for
professionals in insurance and government.
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 Edition provides a comprehensive
and up-to-date introduction to regression modeling for
time-to-event data in medical, epidemiological, biostatistical, and
other health-related research.
This book places a unique emphasis on the practical and
contemporary applications of regression modeling rather than the
mathematical theory. It offers a clear and accessible presentation
of modern modeling techniques supplemented with real-world examples
and case studies. Key topics covered include: variable selection,
identification of the scale of continuous covariates, the role of
interactions in the model, assessment of fit and model assumptions,
regression diagnostics, recurrent event models, frailty models,
additive models, competing risk models, and missing data.
Features of the Second Edition include:
* Expanded coverage of interactions and the covariate-adjusted
survival functions
* The use of the Worchester Heart Attack Study as the main
modeling data set for illustrating discussed concepts and
techniques
* New discussion of variable selection with multivariable
fractional polynomials
* Further exploration of time-varying covariates, complex with
examples
* Additional treatment of the exponential, Weibull, and
log-logistic parametric regression models
* Increased emphasis on interpreting and using results as well as
utilizing multiple imputation methods to analyze data with missing
values
* New examples and exercises at the end of each chapter
Analyses throughout the text are performed using Stata®
Version 9, and an accompanying FTP site contains the data sets used
in the book. Applied Survival Analysis, Second Edition is an ideal
book for graduate-level courses in biostatistics, statistics, and
epidemiologic methods. It also serves as a valuable reference for
practitioners and researchers in any health-related field or for
professionals in insurance and government.
Inhaltsverzeichnis zu „Applied Survival Analysis / Wiley Series in Probability and Statistics (ePub)“
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 Model. 3.4 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 hazard. 5.2.2 An example of purposeful selection of covariates. 5.3 Stepwise, Best-Subsets and Multivariable Fractional Polynomial Methods 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 Subjects. 6.5 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
... mehr
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 Topics. 9.1 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.
... weniger
Autoren-Porträt von David W. Hosmer, Stanley Lemeshow, Susanne May
David W. Hosmer, PhD, is Professor Emeritus of Biostatisticsin the School of Public Health and Heatlth Sciences at the
University of Massachusetts Amherst. Dr. Hosmer is the coauthor of
Applied Logistic Regression, published by Wiley.
Stanley Lemeshow, PhD, is Professor and Dean of the
College of Public Health at The Ohio State University. Dr. Lemeshow
has over thirty-five years of academic experience in the areas of
regression, categorical data methods, and sampling methods. He is
the coauthor of Sampling of Population: Methods and
Application and Applied Logistic Regression, both
published by Wiley.
Susanne May, PhD, is Assistant Professor of Biostatistics
at the University of California, San Diego. Dr. May has over twelve
years of experience in providing statistical support for
health-related research projects.
Bibliographische Angaben
- Autoren: David W. Hosmer , Stanley Lemeshow , Susanne May
- 2011, 2. Auflage, 416 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118211588
- ISBN-13: 9781118211588
- Erscheinungsdatum: 23.09.2011
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: ePub
- Grösse: 12 MB
- Mit Kopierschutz
Sprache:
Englisch
Kopierschutz
Dieses eBook können Sie uneingeschränkt auf allen Geräten der tolino Familie lesen. Zum Lesen auf sonstigen eReadern und am PC benötigen Sie eine Adobe ID.
Kommentar zu "Applied Survival Analysis / Wiley Series in Probability and Statistics"
0 Gebrauchte Artikel zu „Applied Survival Analysis / Wiley Series in Probability and Statistics“
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Applied Survival Analysis / Wiley Series in Probability and Statistics".
Kommentar verfassen