Measures Of Association And Regression Models For Ordinal Variables
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Measures Of Association And Regression Models For Ordinal Variables
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Author : Yi-Lin Chiu
language : en
Publisher:
Release Date : 1997
Measures Of Association And Regression Models For Ordinal Variables written by Yi-Lin Chiu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
To allow statistical inferences, this research finds large sample normality and derives asymptotic standard error formulas for measures of association and regression coefficients in multiple dimensions. The consistency of the estimators for asymptotic standard errors is also proven.
Statistical Models For Ordinal Variables
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Author : Clifford C. Clogg
language : en
Publisher: SAGE Publications, Incorporated
Release Date : 1994-02-28
Statistical Models For Ordinal Variables written by Clifford C. Clogg and has been published by SAGE Publications, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-02-28 with Mathematics categories.
How should data involving response variables of many ordered categories be analyzed? What technique would be most useful in analyzing partially ordered variables regarded as dependent variables? Addressing these and other related concerns in social and survey research, Clogg and Shihadeh explore the statistical analysis of data involving dependent variables that can be coded into discrete, ordered categories, such as "agree," "uncertain," "disagree," or in other similar ways. The authors emphasize the applications of new models and methods for the analysis of ordinal variables and cover general procedures for assessing goodness-of-fit, review the independence model and the saturated model, define measures of association, demonstrate the logit versions of the model, and develop association models as well as logit-type regression models. Aimed at helping researchers formulate models that take account of the ordering of the levels of the variables, this book is appropriate for readers familiar with log-linear analysis and logit regression.
Analysis Of Ordinal Categorical Data
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Author : Alan Agresti
language : en
Publisher: John Wiley & Sons
Release Date : 2012-07-06
Analysis Of Ordinal Categorical Data written by Alan Agresti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-06 with Mathematics categories.
Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments and recent methods. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. Practitioners of statistics in government, industry (particularly pharmaceutical), and academia will want this new edition.
Analysis Of Ordinal Data
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Author : David K. Hildebrand
language : en
Publisher: SAGE
Release Date : 1977
Analysis Of Ordinal Data written by David K. Hildebrand and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Electronic books categories.
Ordinal data can be rank ordered but not assumed to have equal distances between categories. Using support by judges for civil rights measures and bussing as the primary example, this paper indicates how such data can best be analyzed.
Logistic Regression Models For Ordinal Response Variables
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Author : Ann A. O'Connell
language : en
Publisher: SAGE
Release Date : 2006
Logistic Regression Models For Ordinal Response Variables written by Ann A. O'Connell and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Quantitative Social Science Data With R
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Author : Brian J. Fogarty
language : en
Publisher: SAGE
Release Date : 2018-11-24
Quantitative Social Science Data With R written by Brian J. Fogarty and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-24 with Social Science categories.
"One of the few books that provide an accessible introduction to quantitative data analysis with R. A particular strength of the text is the focus on ′real world′ examples which help students to understand why they are learning these methods." - Dr Roxanne Connelly, University of York Relevant, engaging, and packed with student-focused learning features, this book provides the step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and R, it uses examples from across the social sciences to show you how to apply abstract statistical and methodological principles to your own work. At a student-friendly pace, it enables you to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives you not only the tools you need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what you have learned.
Ordinal Regression Models
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Author : Richard A. Williams
language : en
Publisher:
Release Date : 2020
Ordinal Regression Models written by Richard A. Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Anthropology categories.
Researchers often encounter ordinal measures that they wish to examine as dependent variables in their research - variables where the categories are ordered (running from high to low or low to high), but the distance between the categories is unknown. For example, respondents might be asked if they strongly disagree, disagree, agree, or strongly agree with a statement. Or, rather than give an exact value for their years of education, respondents might be asked whether they had no education, some grade school, grade school graduate, some high school, and so on. While it might be tempting to treat ordinal dependent variables as though they were continuous and use techniques like ordinary least squares regression, this can result in misleading estimates of independent variable effects and incorrect tests of statistical significance. Ordinal regression models are therefore preferred under these circumstances - but there are many ordinal models to choose from. This entry begins with a detailed discussion of perhaps the most popular choice, the ordered logit model (also called the proportional odds model). The discussion will cover when the model might be appropriate, the major assumptions of the model (and how they can be violated), and how to interpret model results. However, in many cases, other ordinal models and methods will be more powerful or appropriate. This entry therefore also discusses the ordered probit model, the generalized ordered logit model, interval regression, scoring methods, heterogeneous choice/location scale models, stereotype models, stage models, and the rank-ordered logit model - as well as briefly explains when and why each might be preferred.
Logistic Regression
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Author : Scott W. Menard
language : en
Publisher: SAGE
Release Date : 2010
Logistic Regression written by Scott W. Menard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
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.
Structural Equations With Latent Variables
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Author : Kenneth A. Bollen
language : en
Publisher: John Wiley & Sons
Release Date : 1989-05-12
Structural Equations With Latent Variables written by Kenneth A. Bollen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-05-12 with Mathematics categories.
Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods and contains an integrated comparison of the available strategies for analyzing ordinal data. This is a case study work with illuminating examples taken from across the wide spectrum of ordinal categorical applications. 1984 (0 471-89055-3) 287 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch This book provides the practicing statistician and econometrician with new tools for assessing the quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are either unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data and help to identify the variables involved in each; and pinpoint the estimated coefficients that are potentially most adversely affected. The primary emphasis of these contributions is on diagnostics, but suggestions for remedial action are given and illustrated. 1980 (0 471-05856-4) 292 pp. Applied Regression Analysis Second Edition Norman Draper and Harry Smith Featuring a significant expansion of material reflecting recent advances, here is a complete and up-to-date introduction to the fundamentals of regression analysis, focusing on understanding the latest concepts and applications of these methods. The authors thoroughly explore the fitting and checking of both linear and nonlinear regression models, using small or large data sets and pocket or high-speed computing equipment. Features added to this Second Edition include the practical implications of linear regression; the Durbin-Watson test for serial correlation; families of transformations; inverse, ridge, latent root and robust regression; and nonlinear growth models. Includes many new exercises and worked examples. 1981 (0 471-02995-5) 709 pp.
A Beginner S Guide To Statistics For Criminology And Criminal Justice Using R
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Author : Alese Wooditch
language : en
Publisher: Springer Nature
Release Date : 2021-06-03
A Beginner S Guide To Statistics For Criminology And Criminal Justice Using R written by Alese Wooditch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-03 with Social Science categories.
This book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R. It offers a step-by-step guide for beginners to become familiar with the RStudio platform and tidyverse set of packages. This volume will help users master the fundamentals of the R programming language, providing tutorials in each chapter that lay out research questions and hypotheses centering around a real criminal justice dataset, such as data from the National Survey on Drug Use and Health, National Crime Victimization Survey, Youth Risk Behavior Surveillance System, The Monitoring the Future Study, and The National Youth Survey. Users will also learn how to manipulate common sources of agency data, such as calls-for-service (CFS) data. The end of each chapter includes exercises that reinforce the R tutorial examples, designed to help master the software as well as to provide practice on statistical concepts, data analysis, and interpretation of results. The text can be used as a stand-alone guide to learning R or it can be used as a companion guide to an introductory statistics textbook, such as Basic Statistics in Criminal Justice (2020).