In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

9.1.3 Model quality and statistical significance. We will come back to the question of whether the linear model is valid (whether it satisfies the assumptions of the technique). First we want to ...

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

If just one variable affects the dependent variable, a simple linear regression model is sufficient. If, on the other hand, more than one thing affects that variable, MLR is needed.

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 ...

In simple linear regression 1, we model how the mean of variable Y depends linearly on the value of a predictor variable X; this relationship is expressed as the conditional expectation E(Y|X ...

This paper provides a systematic analysis of identification in linear social interactions models. This is a theoretical and econometric exercise as the analysis is linked to a rigorously delineated ...