Applied Logistic Regression, Second Edition: Book and Solutions Manual Set PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Applied Logistic Regression, Second Edition: Book and Solutions Manual Set PDF full book. Access full book title Applied Logistic Regression, Second Edition: Book and Solutions Manual Set by David W. Hosmer, Jr.. Download full books in PDF and EPUB format.
Author: David W. Hosmer, Jr.
Publisher: Wiley-Interscience
ISBN: 9780471225898
Category : Mathematics
Languages : en
Pages : 0
Get Book Here
Book Description
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models. . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references.
Author: David W. Hosmer, Jr.
Publisher: Wiley-Interscience
ISBN: 9780471225898
Category : Mathematics
Languages : en
Pages : 0
Get Book Here
Book Description
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models. . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references.
Author: Patricia Berglund
Publisher: SAS Institute
ISBN: 162959203X
Category : Computers
Languages : en
Pages : 328
Get Book Here
Book Description
Find guidance on using SAS for multiple imputation and solving common missing data issues. Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data. Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results. Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures. Discover the theoretical background and see extensive applications of the multiple imputation process in action. This book is part of the SAS Press program.
Author: Paul D. Allison
Publisher: SAS Institute
ISBN: 1629590185
Category : Computers
Languages : en
Pages : 348
Get Book Here
Book Description
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.
Author: Christophe Lalanne
Publisher: Elsevier
ISBN: 0081011717
Category : Mathematics
Languages : en
Pages : 176
Get Book Here
Book Description
This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. - Presents the use of SAS software in the statistical approach for the management of data modeling - Includes elements of the language and descriptive statistics - Supplies measures of association, comparison of means, and proportions for two or more samples - Explores linear and logistic regression - Provides survival data analysis
Author:
Publisher:
ISBN: 9781642954876
Category :
Languages : en
Pages : 142
Get Book Here
Book Description
This special collection of SAS Global Forum papers demonstrates new and enhanced capabilities and applications of lesser-known SAS/STAT and SAS Viya procedures for regression models. The goal here is to raise awareness of current valuable SAS/STAT content of which the user may not be aware. Also available free as a PDF from sas.com/books.
Author: Ron Klimberg
Publisher: SAS Institute
ISBN: 1629608033
Category : Computers
Languages : en
Pages : 406
Get Book Here
Book Description
Going beyond the theoretical foundation, this step-by-step book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. --
Author: Daniel Zelterman
Publisher: Cambridge University Press
ISBN: 1108786545
Category : Medical
Languages : en
Pages : 296
Get Book Here
Book Description
This textbook for students in the health and social sciences covers the basics of linear model methods with a minimum of mathematics, assuming only a pre-calculus background. Numerous examples drawn from the news and current events with an emphasis on health issues, illustrate the concepts in an immediately accessible way. Methods covered include linear regression models, Poisson regression, logistic regression, proportional hazards regression, survival analysis, and nonparametric regression. The author emphasizes interpretation of computer output in terms of the motivating example. All of the R code is provided and carefully explained, allowing readers to quickly apply the methods to their own data. Plenty of exercises help students think about the issues involved in the analysis and its interpretation. Code and datasets are available for download from the book's website at www.cambridge.org/zelterman
Author: Scott Menard
Publisher: SAGE
ISBN: 9780761922087
Category : Mathematics
Languages : en
Pages : 130
Get Book Here
Book Description
The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
Author: J. Scott Long
Publisher: SAGE
ISBN: 9780803973749
Category : Mathematics
Languages : en
Pages : 334
Get Book Here
Book Description
Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
Author: Kattamuri S. Sarma
Publisher: SAS Institute
ISBN: 163526040X
Category : Computers
Languages : en
Pages : 574
Get Book Here
Book Description
« Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--
