Regression Models for Categorical Dependent Variables Using Stata, 2nd Edition, by J. Scott Long and Jeremy Freese, shows how to fit and interpret regression models for categorical data with Stata. Nearly 50% longer than the previous edition, the book covers new topics for fitting and interpretating models included in Stata 9, such as multinomial probit models, the stereotype logistic model, and zero-truncated count models. Many of the interpretation techniques have been updated to include interval as well as point estimates.Stata, categorical variables, multinomial logit, stereotype logistic, zero-truncated count
The categorized data that will be analyzed in this paper will be of the type that will use the logis...
This document summarizes the basics of categorical dependent variable models and illustrates how to ...
Introduction and OverviewThe Nature of Limited Dependent VariablesOverview of GLMsEstimation Methods...
This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Editi...
This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Editi...
This article reviews Regression Models for Categorical Dependent Variables Using Stata by Long and F...
Social science and behavioral science students and researchers are often confronted with data that a...
The general linear model, which incorporates statistical analyses, such as ordinary least squares re...
The regression model with categorical dependent variable is a natural generalization of the model wi...
This document summarizes regression models for categorical dependent variables and illustrate
This document summarizes logit and probit regression models for ordinal and nominal dependent variab...
A short post to get back - for my nonlife insurance course - on the interpretation of the output of ...
Social and biological scientists widely use logit (logistic) regression to model binary dependent va...
A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count da...
A short post to get back - for my nonlife insurance course - on the interpretation of the output of ...
The categorized data that will be analyzed in this paper will be of the type that will use the logis...
This document summarizes the basics of categorical dependent variable models and illustrates how to ...
Introduction and OverviewThe Nature of Limited Dependent VariablesOverview of GLMsEstimation Methods...
This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Editi...
This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Editi...
This article reviews Regression Models for Categorical Dependent Variables Using Stata by Long and F...
Social science and behavioral science students and researchers are often confronted with data that a...
The general linear model, which incorporates statistical analyses, such as ordinary least squares re...
The regression model with categorical dependent variable is a natural generalization of the model wi...
This document summarizes regression models for categorical dependent variables and illustrate
This document summarizes logit and probit regression models for ordinal and nominal dependent variab...
A short post to get back - for my nonlife insurance course - on the interpretation of the output of ...
Social and biological scientists widely use logit (logistic) regression to model binary dependent va...
A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count da...
A short post to get back - for my nonlife insurance course - on the interpretation of the output of ...
The categorized data that will be analyzed in this paper will be of the type that will use the logis...
This document summarizes the basics of categorical dependent variable models and illustrates how to ...
Introduction and OverviewThe Nature of Limited Dependent VariablesOverview of GLMsEstimation Methods...