In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

This note discusses a problem that might occur when forward stepwise regression is used for variable selection and among the candidate variables is a categorical variable with more than two categories ...

This family includes models for categorical data such as logistic, probit, and complementary log-log regression for binomial data and Poisson regression for count data, as well as continuous models ...

Based on a statistic proposed by Cook (1977) for the detection of influential observations, we propose a measure for the influence of variables in linear-regression models, and we introduce the ...

This pattern is an example of positive autocorrelation. Time series regression usually involves independent variables other than a time-trend. However, the simple time-trend model is convenient for ...

Course TopicsOrdinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be discrete (e.g ...

Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous ...