The teaching of logit regression analysis is much neglected in statistics courses within sociology. This is unfortunate since it is well-suited to so many data analysis situations within the discipline. We often run into cases in the real world when the dependent variable is dichotomous. Researchers often deal with such situations by using discriminant analysis, weighted least squares regression, or ordinary least squares regression. These methods can lead to misinterpretations of the results. Logit regression allows the researcher to evaluate the impact of a set of predictor variables on a dichotomous dependent variable without these problems. It is a relatively simple technique to understand for those who already have a grasp on the logic...
The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal...
Nonlinear statistical models, of which logistic regression is one example, are often used in applied...
While it is common practice for researchers in psychology and other social sciences to use inferent...
This article is in the form of a short tutorial discussion, presenting the logistic (logit)regressio...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
These presentations cover both binary and multinomial logistic regression and use examples from the ...
This text offers an introduction to binary logistic regression, a confirmatory technique for statist...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation b...
Linear regression is a statistical procedure for calculating the value of a dependent variable from ...
This textbook considers statistical learning applications when interest centers on the conditional d...
This volume presents in detail the fundamental theories of linear regression analysis and diagnosis,...
This document summarizes logit and probit regression models for ordinal and nominal dependent variab...
Das Skript beschreibt die Durchführung von binär-logistischen Regressionsanalysen in den Sozialwisse...
This textbook provides students and professionals in the health sciences with a presentation of the ...
The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal...
Nonlinear statistical models, of which logistic regression is one example, are often used in applied...
While it is common practice for researchers in psychology and other social sciences to use inferent...
This article is in the form of a short tutorial discussion, presenting the logistic (logit)regressio...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
These presentations cover both binary and multinomial logistic regression and use examples from the ...
This text offers an introduction to binary logistic regression, a confirmatory technique for statist...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation b...
Linear regression is a statistical procedure for calculating the value of a dependent variable from ...
This textbook considers statistical learning applications when interest centers on the conditional d...
This volume presents in detail the fundamental theories of linear regression analysis and diagnosis,...
This document summarizes logit and probit regression models for ordinal and nominal dependent variab...
Das Skript beschreibt die Durchführung von binär-logistischen Regressionsanalysen in den Sozialwisse...
This textbook provides students and professionals in the health sciences with a presentation of the ...
The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal...
Nonlinear statistical models, of which logistic regression is one example, are often used in applied...
While it is common practice for researchers in psychology and other social sciences to use inferent...