Applied Logistic Regression

8.2 ORDINAL LOGISTIC REGRESSION MODELS 8.2.1 Introduction to the Models, Methods for Fitting and Interpretation of Model Parameters There are occasions when the scale of a multiple category outcome is not nominal but ordinal.

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9780471654025

Category: Mathematics

Page: 392

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Logistic Regression

Logistic regression models ( sometimes also called logit models ) thus estimate the linear determinants of the logged odds or logit rather than the nonlinear determinants of probabilities . Obtaining these estimates involves ...

Author: Fred C. Pampel

Publisher: SAGE

ISBN: 0761920102

Category: Social Science

Page: 85

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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
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Applied Logistic Regression Analysis

AN INTRODUCTION TO LOGISTIC REGRESSION DIAGNOSTICS When the assumptions of logistic regression analysis are violated , calculation of a logistic regression model may result in one of three problematic effects : biased coefficients ...

Author: Scott Menard

Publisher: SAGE

ISBN: 0761922083

Category: Mathematics

Page: 130

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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.
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Interaction Effects in Logistic Regression

As noted , Equation 4 is similar to that of the traditional linear regression model . ... Categorical Predictors and Dummy Variables Logistic regression analysis often includes categorical variables as predictors , such as gender ...

Author: James Jaccard

Publisher: SAGE

ISBN: 0761922075

Category: Mathematics

Page: 84

View: 299

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This work introduces general strategies for testing interactions in logistic regression as well as providing the tools to interpret and understand the meaning of coefficients in equations with product terms.
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Logistic Regression Models for Ordinal Response Variables

Measures of Association There are several logistic regression analogs to the familiar model R from ordinary least squares regression that may be useful for informing about strength of association between the collection of independent ...

Author: Ann A. O'Connell

Publisher: SAGE

ISBN: 0761929894

Category: Mathematics

Page: 107

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Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
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Logistic Regression

regressiOn. mOdeL. Table 10.6 illustrates the stereotype regression model. Typically, a single equation model is estimated; but it is possible to specify the number of dimensions or logistic functions to be computed, and setting the ...

Author: Scott Menard

Publisher: SAGE

ISBN: 9781412974837

Category: Social Science

Page: 377

View: 223

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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.
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Misclassification in Logistic Regression

Lecture Notes on Nonparametric Statistical Inference. Columbia University. Pregibon, D. (1981). Logistic regression diagnostics. Ann. Statist. 9, 705–724. Rao, C. R. (1973). Linear Statistical Inference and Its Applications.

Author: Shane Phillip Pederson

Publisher:

ISBN: MINN:31951001300132V

Category: Regression analysis

Page: 468

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Applied Logistic Regression

Use the ICU data described in Section 1.6.1 and consider the multiple logistic regression model of vital status, STA, on age (AGE), cancer part of the present problem (CAN), CPR prior to ICU admission (CPR), infection probable at ICU ...

Author: David W. Hosmer, Jr.

Publisher: John Wiley & Sons

ISBN: 9781118548356

Category: Mathematics

Page: 528

View: 741

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A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
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Logistic Regression Using SAS

Allison, Paul D. Logistic Regression Using SAS®: Theory and Application, Second Edition. ... MODEL statement (LOGISTIC) binary logistic regression and 64–65 logistic regression for ordered categories and 173 logit analysis of ...

Author: Paul D. Allison

Publisher: SAS Institute

ISBN: 9781629590189

Category: Computers

Page: 348

View: 110

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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.
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Applied Ordinal Logistic Regression Using Stata

For detailed guidelines and recommendations on reporting the results of logistic regression, see Peng, Lee, and Ingersoll (2002). In addition, O'Connell and Amico (2010) provided a list of key elements of logistic regression that should ...

Author: Xing Liu

Publisher: SAGE Publications

ISBN: 9781483319766

Category: Social Science

Page: 552

View: 812

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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. 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.
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