Making individual predictions If we know the value of several explanatory variables for an individual, but do not know the value of that individual’s dependent variable, we can use the prediction ...

Applied economists have long struggled with the question of how to accommodate binary endogenous regressors in models with binary and nonnegative outcomes. I argue here that much of the difficulty ...

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 ...

The empirical model may also be used to construct a way to forecast the dependent variable, potentially helping policymakers make decisions about changes in monetary and/or fiscal policy to keep the ...

A lack of homoskedasticity may suggest that the regression model may need to include additional predictor variables to explain the performance of the dependent variable.

This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to ...

The short course will illustrate how to use JMP in linear regression analysis. The three main topics will be: Exploratory data analysis, simple liner regression and polynomial regression How to fit a ...

The empirical model may also be used to construct a way to forecast the dependent variable, potentially helping policymakers make decisions about changes in monetary and/or fiscal policy to keep the ...

And, in fact, if you combine the intercept estimate with the estimate for non-Hispanic blacks, you get 49.3–23.7 = 25.6, exactly what we saw in the simple tabulation above. Multiple regression models ...