Melamed, David M.,
Applications of regression for categorical outcomes using R / David Melamed and Long Doan. - xv, 222 pages : color illustrations ; 24 cm
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"--
9780367894634 9781032509518
2022060984
Regression analysis--Mathematical models.
Linear models (Statistics)
Social sciences--Statistical methods.
R (Computer program language)
HA31.3 / .M44 2023
519.5/36 , On Display 23
Applications of regression for categorical outcomes using R / David Melamed and Long Doan. - xv, 222 pages : color illustrations ; 24 cm
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"--
9780367894634 9781032509518
2022060984
Regression analysis--Mathematical models.
Linear models (Statistics)
Social sciences--Statistical methods.
R (Computer program language)
HA31.3 / .M44 2023
519.5/36 , On Display 23