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1 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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