Compare and contrast three types of regression models for categorical data : log-linear, logistic, and multinomial. Learn how to choose the best model for your research question.

When you perform log-linear model analysis, you can request weighted least-squares estimates, maximum likelihood estimates, or both. By default, PROC CATMOD calculates maximum likelihood estimates ...

Regression analysis on log-transformed data estimates the relative effect, whereas it is often the absolute effect of a predictor that is of interest. We propose a maximum likelihood (ML)-based ...

9.1.4 Interpretation. You should be getting comfortable with the output from statistical packages by now (having used regression in Excel and SAS). The summary function in R starts with a five-number ...

A linear regression essentially estimates a line of best fit among all variables in the model. Regression analysis may be robust if the variables are independent, there is no heteroscedasticity ...

In this article, you'll learn the basics of simple linear regression, sometimes called 'ordinary least squares' or OLS regression—a tool commonly used in forecasting and financial analysis. We ...

This note explains how to choose between log and linear specification. The note emphasizes the economic interpretation of a log model and how to interpret coefficients in a log regression. The note ...

Although the interpretation of β j seems to be identical to its interpretation in the simple linear regression model, the innocuous phrase “and others are held constant” turns out to have ...