Best Practices in Logistic Regression
Title | Best Practices in Logistic Regression PDF eBook |
Author | Jason W. Osborne |
Publisher | SAGE Publications |
Pages | 489 |
Release | 2014-02-26 |
Genre | Social Science |
ISBN | 1483323137 |
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. Best Practices in Logistic Regression explains logistic regression in a concise and simple manner that gives students the clarity they need without the extra weight of longer, high-level texts.
Regression & Linear Modeling
Title | Regression & Linear Modeling PDF eBook |
Author | Jason W. Osborne |
Publisher | SAGE Publications |
Pages | 489 |
Release | 2016-03-24 |
Genre | Psychology |
ISBN | 1506302750 |
In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.
Best Practices in Quantitative Methods
Title | Best Practices in Quantitative Methods PDF eBook |
Author | Jason W. Osborne |
Publisher | SAGE |
Pages | 609 |
Release | 2008 |
Genre | Social Science |
ISBN | 1412940656 |
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Best Practices in Logistic Regression
Title | Best Practices in Logistic Regression PDF eBook |
Author | Jason W. Osborne |
Publisher | SAGE Publications |
Pages | 489 |
Release | 2014-02-26 |
Genre | Social Science |
ISBN | 1483312097 |
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.
Studyguide for Best Practices in Logistic Regression by Osborne, Jason W., ISBN 9781452244792
Title | Studyguide for Best Practices in Logistic Regression by Osborne, Jason W., ISBN 9781452244792 PDF eBook |
Author | Cram101 Textbook Reviews |
Publisher | Cram101 |
Pages | 92 |
Release | 2014-05-02 |
Genre | |
ISBN | 9781497005242 |
Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9781452244792. This item is printed on demand.
Applied Logistic Regression
Title | Applied Logistic Regression PDF eBook |
Author | David W. Hosmer, Jr. |
Publisher | John Wiley & Sons |
Pages | 397 |
Release | 2004-10-28 |
Genre | Mathematics |
ISBN | 0471654027 |
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.
Logistic Regression
Title | Logistic Regression PDF eBook |
Author | Scott W. Menard |
Publisher | SAGE |
Pages | 393 |
Release | 2010 |
Genre | Mathematics |
ISBN | 1412974836 |
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.