Nicholas J. Horton, Nan M. Laird, Maximum Likelihood Analysis of Logistic Regression Models with Incomplete Covariate Data and Auxiliary Information ... provides a general method for estimating ...

Abstract. Characterizing model identifiability in the presence of missing covariate data is a very important issue in missing data problems. In this article, we characterize the propriety of the ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

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 ...

Building a linear regression model. So far, I have explored the dataset in detail and got familiar with it. Now it is time to create the model and see if I can predict Yearly Amount Spent.