MODEL SELECTION (VIRTUAL)

Often, researchers have too many variables for their statistical model, need to have a clearer idea of which variables contribute the most to the research question, or are not sure that model selection is even the correct approach to take.

By the end of this workshop, attendees will be able to:

• Identify different methods for choosing the appropriate model including testing based and criterion-based approaches

• Understand when model selection is not necessary

• Explain tools used for model selection, error identification, and information criteria