title: Estimating regression standard errors with data from the Current Population Survey's public use file.
abstract: This study examines whether reasonable standard errors for multivariate models can be calculated using the public use file of the Current Population Survey's Annual Social and Economic Supplement (CPS ASEC). We restrict our analysis to the 2003 CPS ASEC and model three dependent variables at the individual level. income, poverty, and health insurance coverage. We compare standard error estimates performed on the CPS ASEC public use file with those obtained from the Census Bureau's restricted internal data that include all the relevant sampling information needed to compute standard errors adjusted for the complex survey sample design. Our analysis shows that the multivariate standard error estimates derived from the public use CPS ASEC following our specification perform relatively well compared to the estimates derived from the internal Census Bureau file. However, it is essential that users of CPS ASEC data do not simply choose any available method since three of the methods commonly used for adjusting for the complex sample design produce substantially different estimates.
authors.affiliation: School of Public Health, University of Minnesota, Minneapolis, MN 55414, USA. daver004@umn.edu
authors.forename: Michael
authors.initials: M
authors.lastname: Davern
authors.forename: Arthur
authors.initials: A
authors.lastname: Jones
authors.forename: James
authors.initials: J
authors.lastname: Lepkowski
authors.forename: Gestur
authors.initials: G
authors.lastname: Davidson
authors.forename: Lynn A
authors.initials: LA
authors.lastname: Blewett
mesh_terms: D016208:Databases, Factual; D006302:Health Services Research / Q000379:methods*; D006306:Health Surveys; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data / Q000639:trends; D007348:Insurance, Health / Q000706:statistics & numerical data / Q000639:trends*; D016015:Logistic Models; D015999:Multivariate Analysis; D011203:Poverty / Q000706:statistics & numerical data / Q000639:trends; D015203:Reproducibility of Results; D014481:United States