… For each outcome variable, I report the results of linear and logistic regression. Specifically,
… That is, I report ORs for logistic regression and the ATE in probabilities for linear regression. …

… A continuous outcome variable can be converted to a categorical one in order for logistic …
Unlike linear regression, the predictor variables in logistic regression do not need to be …

… This book examines log-linear models for contingency tables. Logistic regression and
logistic discrimination are treated as special cases and generalized linear models (in the GLIM …

… will discuss linear regression analysis for the examination of continuous outcome data and
logistic … Furthermore, we focus on the most important application of multiple linear and logistic …

SciELO - Brasil - Linear and logistic regression models: when to use and how to interpret
them? Linear and logistic regression models: when to use and how to interpret them? …

… a logistic general linear model (8). In this study, we compared the goodness of fit of linear
regression to logistic … models using both the logistic and linear approaches in exactly the same …

The present paper consists of a theoretical and an empirical part: First Rasch's test model for
items with two answer categories is considered under the assumption of linear constraints …

… test model is an extension of the Rasch model where certain linear constraints are imposed
… BTL with linear restrictions imposed on the BTL parameters, which we denote as the 'Linear …

… In the early seventies, in applications of the linear logistic test model (LLTM) the emphasis
… The model discussed in this section has therefore been called the 'linear logistic model with …

… linear test is of little practical importance. The significance probabilities from linear and logistic
… A comparison between the results of linear and logistic measures is made, and reasons …