1 / 8

Biostatistics-Lecture 7 Variable selection methods

Biostatistics-Lecture 7 Variable selection methods. Ruibin Xi Peking University School of Mathematical Sciences. Stepwise selection. Backward Elimination. Stepwise selection. For ward Selection. Drawbacks of stepwise selection. One-at-a-time: may miss optimal

shauna
Download Presentation

Biostatistics-Lecture 7 Variable selection methods

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Biostatistics-Lecture 7Variable selection methods Ruibin Xi Peking University School of Mathematical Sciences

  2. Stepwise selection • Backward Elimination

  3. Stepwise selection • Forward Selection

  4. Drawbacks of stepwise selection • One-at-a-time: may miss optimal • P-values of the remaining predictors tends to be overstated • Multiple testing • Model tends to be smaller than desirable for prediction purpose • Variable not in the model may still be correlated with the response

  5. Stepwise selection—An example • Interested in factors related to the life expectancy (50 US states,1969-71 ) • Per capita income (1974) • Illiteracy (1970,percent of population) • Murder rate per 100,000 population • Percent high-school graduates • Mean number of days with min temperature < 30 degree • Land area in square mile

  6. Criterion-based procedures • The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) • Adjusted R2—Ra2

  7. Criterion-based procedures • Mallow’s Cp statistic: • The mean squared prediction error (MSPE) • Can be estimated by • Under true model

  8. Penalized methods • Ridge regression • Lasso • ElasticNet

More Related