Applications of regression for categorical outcomes using R / David Melamed and Long Doan.
By: Melamed, David M [author.].
Contributor(s): Doan, Long [author.].
Material type:
BookPublisher: Boca Raton ; London : CRC Press Taylor & Francis Group, CRC Press is an imprint of the Taylor & Francis Group, an informa business, A Chapman & Hall Book, 2024.Description: xv, 222 pages : color illustrations ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780367894634; 9781032509518.Subject(s): Regression analysis -- Mathematical models | Linear models (Statistics) | Social sciences -- Statistical methods | R (Computer program language)DDC classification: 519.5/36 Summary: "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"-- Provided by publisher.
| Item type | Current location | Call number | Copy number | Status | Date due |
|---|---|---|---|---|---|
Monograph
|
Indian Institute of Management Udaipur On Display | 519.536 (Browse shelf) | 1 | Available |
Includes bibkiographical references and index.
"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"-- Provided by publisher.
There are no comments for this item.