Comparison of subset selection methods in linear regression in the context of health-related quality of life and substance abuse in Russia

摘要

BackgroundAutomatic stepwise subset selection methods in linear regression often perform poorly, both in terms of variable selection and estimation of coefficients and standard errors, especially when number of independent variables is large and multicollinearity is present. Yet, stepwise algorithms remain the dominant method in medical and epidemiological research.