Part1

Nonlinear models pose the challenge of overfitting. Provide an example in which overfitting could significantly affect the outcome of the analysis and explain why this is the case. Review examples submitted by your classmates and suggest statistical methods to mitigate the overfitting described in their models.

Part 2

Familiarize yourself with the following models:

1. Nonlinear regression
2. The process of analyzing nested or clustered data
3. Regularization methods

Describe a scenario for each of the three models.

Generate synthetic data suitable for analysis in each one of the scenarios.

Develop a scenario that involves complex data with multiple predictors for a response variable.

1. Your scenario should include multiple categorical variables that can be nested or crossed, depending on how data is collected.
2. Explain how you would control for random effects.
3. Describe the value of mixed-effect models when analyzing nested or crossed data structures.