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Applications of regression for categorical outcomes using R /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applications of regression for categorical outcomes using R /David Melamed and Long Doan.
作者:	Melamed, David M.,
其他作者:	Doan, Long,
面頁冊數:	1 online resource (xv, 222 pages) :illustrations (some color)
標題:	Regression analysisMathematical models.
ISBN:	9781003029847$qelectronic book

Applications of regression for categorical outcomes using R /
Melamed, David M.,

Applications of regression for categorical outcomes using R /David Melamed and Long Doan. - First edition. - 1 online resource (xv, 222 pages) :illustrations (some color)

Includes bibliographical references and index.

Introduction to R studio and packages -- Overview of OLS regression and introduction to general linear model -- Describing categorical variables and some useful tests of association -- Regression for binary outcomes -- Regression for binary outcomes : moderation and squared terms moderation -- Regression for ordinal outcomes -- Regression for nominal outcomes -- Regression for count outcomes -- Additional outcome types -- Special topics : comparing between models and missing data.

"This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata, SPSS and SAS, to using R, and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge, and for Quantitative social scientists due to it's ability to act as a practitioners guide"--

ISBN: 9781003029847$qelectronic book

LCCN: 2022060985Subjects--Topical Terms:

405172
Regression analysis
--Mathematical models.

LC Class. No.: HA31.3 / .M44 2024

Dewey Class. No.: 519.5/36

Applications of regression for categorical outcomes using R /
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100 1 $a Melamed, David M., $e author. $3 966302
245 1 0 $a Applications of regression for categorical outcomes using R / $c David Melamed and Long Doan.
250 $a First edition.
264 1 $a Boca Raton, FL : $b CRC Press, $c 2024.
264 4 $c ©2024
300 $a 1 online resource (xv, 222 pages) : $b illustrations (some color)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
504 $a Includes bibliographical references and index.
505 0 $a Introduction to R studio and packages -- Overview of OLS regression and introduction to general linear model -- Describing categorical variables and some useful tests of association -- Regression for binary outcomes -- Regression for binary outcomes : moderation and squared terms moderation -- Regression for ordinal outcomes -- Regression for nominal outcomes -- Regression for count outcomes -- Additional outcome types -- Special topics : comparing between models and missing data.
520 $a "This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata, SPSS and SAS, to using R, and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge, and for Quantitative social scientists due to it's ability to act as a practitioners guide"-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed on January 09, 2024).
650 0 $a Regression analysis $x Mathematical models. $3 405172
650 0 $a Linear models (Statistics) $3 181866
650 0 $a Social sciences $x Statistical methods. $3 182009
650 0 $a R (Computer program language) $3 210846
650 6 $a Sciences sociales $x Méthodes statistiques. $3 966383
650 6 $a R (Langage de programmation) $3 943796
700 1 $a Doan, Long, $d 1988- $e author. $3 966303
776 0 8 $i Print version: $a Melamed, David M. $t Social science applications of regression for categorical outcomes using R $d Boca Raton : CRC Press, 2023 $z 9780367894634 $w (DLC) 2022060984
994 $a C0 $b TWNUK