Post-selection Inference of High-dimensional Logistic Regression Under Case–Control Design

Confidence sets are of key importance in high-dimensional statistical inference. Under case–control study, a popular response-selective sampling design medical study or econometrics, we consider the confidence intervals and tests for single low-dimensional parameters logistic regression model. The asymptotic properties resulting estimators established under mild conditions. We also testing more general complex hypotheses parameters. procedures proved to be asymptotically exact have satisfactory power. Numerical studies including extensive simulations real data example confirm that proposed method performs well practical settings.