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 ...

Because many common DIF detection methods ignore potential DIF variance, this paper proposes the use of random coefficient hierarchical logistic regression (RC-HLR) models to test for both uniform DIF ...

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.

Gelman and Hill, Data analysis Using Regression and Multilevel/Hierarchical models (CUP, 2007) First part. Neter, J., Kutner, M., Nachtsheim, C. and Wasserman, W. Applied Linear Statistical Models, ...

Often, regression models that appear nonlinear upon first glance are actually linear. The curve estimation procedure can be used to identify the nature of the functional relationships at play in ...

Gelman and Hill, Data analysis Using Regression and Multilevel/Hierarchical models (CUP, 2007) First part. 2. ... Fox (2016) Applied Regression Analysis and Generalized Linear Models. Assessment. Exam ...