It is common when fitting multilevel models to start with a simple model, and build it up by adding new terms and re-estimating the model. If you want to compare the fit of a multilevel model with a simpler variant of the same model, what estimation method must you use?
A)Ordinary least squares
B)Maximum likelihood
C)Restricted maximum likelihood
D)Generalized least squares

Question

Quizplus · Accepted Answer

In order to compare the fit of a multilevel model with a simpler variant of the same model, one must use maximum likelihood estimation method. This method allows for comparing the likelihood of the data under different models, and choosing the one that provides the best fit. Ordinary least squares and generalized least squares are not well-suited for multilevel models, and restricted maximum likelihood is a variant of maximum likelihood that is more commonly used for parameter estimation rather than model comparison.

It Is Common When Fitting Multilevel Models to Start with a Simple