Handbook of the Logistic Distribution, Balakrishnan, N.
Автор: Allison Paul David, Sas Institute Название: Logistic Regression Using SAS: Theory and Application ISBN: 1599946416 ISBN-13(EAN): 9781599946412 Издательство: Неизвестно Цена: 13049.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Informal and nontechnical, this book both explains the theory behind logistic regression, and looks at all the practical details involved in its implementation using SAS. Includes several real-world examples in full detail.
Автор: Hilbe Название: Logistic Regression Models ISBN: 1138106712 ISBN-13(EAN): 9781138106710 Издательство: Taylor&Francis Рейтинг: Цена: 8726.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models to health, environmental, physical, and social science data.
Examples illustrate successful modeling The text first provides basic terminology and concepts, before explaining the foremost methods of estimation (maximum likelihood and IRLS) appropriate for logistic models. It then presents an in-depth discussion of related terminology and examines logistic regression model development and interpretation of the results. After focusing on the construction and interpretation of various interactions, the author evaluates assumptions and goodness-of-fit tests that can be used for model assessment. He also covers binomial logistic regression, varieties of overdispersion, and a number of extensions to the basic binary and binomial logistic model. Both real and simulated data are used to explain and test the concepts involved. The appendices give an overview of marginal effects and discrete change as well as a 30-page tutorial on using Stata commands related to the examples used in the text. Stata is used for most examples while R is provided at the end of the chapters to replicate examples in the text.
Apply the models to your own data Data files for examples and questions used in the text as well as code for user-authored commands are provided on the book's website, formatted in Stata, R, Excel, SAS, SPSS, and Limdep.
See Professor Hilbe discuss the book.
Автор: David G. Kleinbaum; Mitchel Klein Название: Logistic Regression ISBN: 1493936972 ISBN-13(EAN): 9781493936977 Издательство: Springer Рейтинг: Цена: 12571.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This highly readable book describes fundamental and advanced concepts and methods of logistic regression. The 3rd edition includes three new chapters, an updated computer appendix, and an expanded section on modeling guidelines that consider causal diagrams.
Автор: Werner Vach Название: Logistic Regression with Missing Values in the Covariates ISBN: 0387942637 ISBN-13(EAN): 9780387942636 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The author reviews the essentials of logistic regression and discusses the variety of mechanisms which might cause missing values while the rest of the book covers the methods which may be used to deal with missing values and their effectiveness.
Описание: If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul Allison's Logistic Regression Using SAS: Theory and Application, Second Edition, is for you Informal and nontechnical, this book both explains the theory behind logistic regression, and looks at all the practical details involved in its implementation using SAS. Several real-world examples are included in full detail. This book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logistic regression, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed. The second edition describes many new features of PROC LOGISTIC, including conditional logistic regression, exact logistic regression, generalized logit models, ROC curves, the ODDSRATIO statement (for analyzing interactions), and the EFFECTPLOT statement (for graphing nonlinear effects). Also new is coverage of PROC SURVEYLOGISTIC (for complex samples), PROC GLIMMIX (for generalized linear mixed models), PROC QLIM (for selection models and heterogeneous logit models), and PROC MDC (for advanced discrete choice models).
This book is part of the SAS Press program.
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