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: <ul>
<li>Expanded coverage of interactions and the covariate-adjusted survival functions</li> <li>The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques</li> <li>New discussion of variable selection with multivariable fractional polynomials</li> <li>Further exploration of time-varying covariates, complex with examples</li> <li>Additional treatment of the exponential, Weibull, and log-logistic parametric regression models</li> <li>Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values</li> <li>New examples and exercises at the end of each chapter</li> </ul>
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.

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

Science & Math

Lemeshow, Stanley

May, Susanne

Hosmer Jr., David W.

Biological Sciences

Wiley-Interscience

Practical Multivariate Analysis (Chapman & Hall/CRC Texts in Statistical Science)

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. 
Key Features:\nProvides a comprehensive, practical and accessible introduction to multivariate analysis.\nKeeps mathematical details to a minimum, so particularly geared toward a non-statistical audience.\nIncludes lots of detailed worked examples, guidance on computing, and exercises.\nUpdated with a new chapter on data visualization.

Clark, Virginia A.

Afifi, Abdelmonem

Donatello, Robin

Reference

Chapman and Hall/CRC

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. 
Key Features: <ul>
<li>Provides a comprehensive, practical and accessible introduction to multivariate analysis. </li> <li>Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. </li> <li>Includes lots of detailed worked examples, guidance on computing, and exercises. </li> <li>Updated with a new chapter on data visualization.</li> </ul>

This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical analyses and understand the results. For each of the techniques presented in this edition, the authors use the most recent software versions available and discuss the most modern ways of performing the analysis. New to the Fifth Edition <ul>
<li>Chapter on regression of correlated outcomes resulting from clustered or longitudinal samples</li> <li>Reorganization of the chapter on data analysis preparation to reflect current software packages</li> <li>Use of R statistical software</li> <li>Updated and reorganized references and summary tables</li> <li>Additional end-of-chapter problems and data sets</li> </ul> The first part of the book provides examples of studies requiring multivariate analysis techniques; discusses characterizing data for analysis, computer programs, data entry, data management, data clean-up, missing values, and transformations; and presents a rough guide to assist in choosing the appropriate multivariate analysis. The second part examines outliers and diagnostics in simple linear regression and looks at how multiple linear regression is employed in practice and as a foundation for understanding a variety of concepts. The final part deals with the core of multivariate analysis, covering canonical correlation, discriminant, logistic regression, survival, principal components, factor, cluster, and log-linear analyses. While the text focuses on the use of R, S-PLUS, SAS, SPSS, Stata, and STATISTICA, other software packages can also be used since the output of most standard statistical programs is explained. Data sets and code are available for download from the book’s web page and CRC Press Online.

Mathematics

Computer-Aided Multivariate Analysis, Fourth Edition enables researchers and students with limited mathematical backgrounds to understand the concepts underlying multivariate statistical analysis, perform analysis using statistical packages, and understand the output. New topics include Loess and Poisson regression, nominal and ordinal logistic regression, interpretation of interactions in logistic and survival analysis, and imputation for missing values. This book includes new exercises and references, and updated options in the latest versions of the statistical packages. All data sets and codebooks are available for download. The authors explain the assumptions made in performing each analysis and test, how to determine if your data meets those assumptions, and what to do if they do not. What to Watch out for sections in each chapter warn of common difficulties. By reading this text, you will know what method to use with your data set, how to get the results, and how to interpret them and explain them to others. New in the Fourth Edition: <ul>
<li>Expanded explanation of checking for goodness of fit in logistic regression and survival analysis</li> <li>Kaplan-Meier estimates of survival curves, formal tests for comparing survival between groups, interactions and the use of time-dependent covariates in survival analysis</li> <li>Expanded discussion of how to handle missing values</li> <li>Latest features of the S-PLUS package in addition to SAS, SPSS, STATA, and STATISTICA for multivariate analysis</li> <li>Data sets for the problems are available at the CRC web site: http://www.crcpress.com/product/isbn/9781584883081</li> <li>Commands and output for examples used in the text for each statistical package are available at the UCLA web site: http://www.ats.ucla.edu/stat/examples/cama4/</li>
</ul>

Computer-Aided Multivariate Analysis, Fourth Edition (Chapman & Hall/CRC Texts in Statistical Science)

See the best price to sell, buy, or rent books by May, Susanne. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by May, Susanne

See the best price to sell, buy, or rent books by May, Susanne. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

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

Practical Multivariate Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Practical Multivariate Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Practical Multivariate Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Computer-Aided Multivariate Analysis, Fourth Edition (Chapman & Hall/CRC Texts in Statistical Science)