Regularized Linear Modeling and Controlled Variable Selection (Knockoff Filtering)
Use the Hearth Attack (CaseStudy12_ AdultsHeartAttack) data to:
- Identify and impute any missing values
- Use the
DIAGNOSIS
as a clinically relevant outcome variable
- Randomly split the data into training (70%) and testing (30%) sets
- Use the LASSO model to standardize the predictors and report the model results
- Optimize the choice of the regularization parameter
- Apply cross validation to report internal statistical validity of the model
- Report and compare the OLS, Stepwise OLS with AIC, Ridge and LASSO coefficient estimates
- Calculate the predicted values for all 4 models and report the models performance
- Apply knockoff filtering to control the false variable selection rate
- Compare the variables selected by Stepwise OLS, LASSO and knockoff
- Apply Bootstrap LASSO and knockoff, and compare the results.
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