Considerable importance is placed on effective modeling strategies and the interpretation and presentation of results. 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.
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models. Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression.
As before, it focuses on easy-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis.
The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research. 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.
Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective.
Learn more. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique.
Annotated screenshots from SPSS and other packages are integrated throughout. Designed for course flexibility, after the first 4 chapters, instructors can use chapters in any sequence or combination to fit the needs of their students. This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the coefficients of interactive logistic models for a wide range of situations encountered in the research literature.
Multiple and generalized nonparametric regression. Hosmer , D. Applied logistic regression 2nd ed. New York : Wiley. Menard , S. Skip to content. Author : David W. Hosmer, Jr. From the reviews of the First Edition. Author : D. Author : Ann A. Author : Mitchell H. Author : Debbie L. Author : Bryan F. Author : Brett G. Author : Laurens Holmes, Jr. Author : Joseph M. Applied logistic regression Wiley Series in probability and statistics Dietz, M.
Gail, K. Krickeberg, A. Tsiatis, J. Samet Springer New Y Your name. Close Send. Remember me Forgot password? Our partners will collect data and use cookies for ad personalization and measurement.
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