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Applied Logistic Regression

Applied Logistic Regression
Author: David W. Hosmer, Jr.
Publisher: John Wiley & Sons
Total Pages: 397
Release: 2004-10-28
Genre: Mathematics
ISBN: 0471654027

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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." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.


Applied Logistic Regression Analysis

Applied Logistic Regression Analysis
Author: Scott Menard
Publisher: SAGE
Total Pages: 130
Release: 2002
Genre: Mathematics
ISBN: 9780761922087

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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.


Applied Logistic Regression Analysis

Applied Logistic Regression Analysis
Author: Scott Menard
Publisher: SAGE Publications, Incorporated
Total Pages: 112
Release: 1995-06-29
Genre: Mathematics
ISBN:

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Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate and multiple linear regression.


Logistic Regression

Logistic Regression
Author: Scott W. Menard
Publisher: SAGE
Total Pages: 393
Release: 2010
Genre: Mathematics
ISBN: 1412974836

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Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.


Applied Survival Analysis

Applied Survival Analysis
Author: David W. Hosmer, Jr.
Publisher: John Wiley & Sons
Total Pages: 285
Release: 2011-09-23
Genre: Mathematics
ISBN: 1118211588

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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.


Applied Logistic Regression, Second Edition: Book and Solutions Manual Set

Applied Logistic Regression, Second Edition: Book and Solutions Manual Set
Author: David W. Hosmer, Jr.
Publisher: Wiley-Interscience
Total Pages: 0
Release: 2001-11-13
Genre: Mathematics
ISBN: 9780471225898

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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.


Best Practices in Logistic Regression

Best Practices in Logistic Regression
Author: Jason W. Osborne
Publisher: SAGE Publications
Total Pages: 489
Release: 2014-02-26
Genre: Social Science
ISBN: 1483312097

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Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.


Applied Logistic Regression Analysis

Applied Logistic Regression Analysis
Author: Scott Menard
Publisher: SAGE Publications, Incorporated
Total Pages: 0
Release: 1995-06-29
Genre: Social Science
ISBN: 9780803957572

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Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate and multiple linear regression.


Applied Ordinal Logistic Regression Using Stata

Applied Ordinal Logistic Regression Using Stata
Author: Xing Liu
Publisher: SAGE Publications
Total Pages: 372
Release: 2015-09-30
Genre: Social Science
ISBN: 1483319768

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The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software. An open-access website for the book contains data sets, Stata code, and answers to in-text questions.


Logistic Regression

Logistic Regression
Author: Fred C. Pampel
Publisher: SAGE
Total Pages: 98
Release: 2000-05-26
Genre: Mathematics
ISBN: 9780761920106

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Trying to determine when to use a logistic regression and how to interpret the coefficients? Frustrated by the technical writing in other books on the topic? Pampel's book offers readers the first "nuts and bolts" approach to doing logist