Estimating Regression Standard Errors with Data from the Current Population Survey's Public Use File
Bibliographic Data
| ID | 13775588 |
|---|---|
| Authors | Michael Davern (0000-0002-9572-812X, University of Minnesota System, corresponding author), Arthur Jones, James M Lepkowski (University of Minnesota System), James Lepkowski, Gestur Davidson (University of Minnesota System), Lynn A Blewett (0000-0003-0409-8394) |
| Year | 2007 |
| Volume | 44 |
| Issue | 2 |
| Pages | 211-224 |
| Publication date | 2007-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | INQUIRY The Journal of Health Care Organization Provision and Financing (JOURNAL) |
| Journal identifiers | ISSN: 0046-9580 • E-ISSN: 1945-7243 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.5034/inquiryjrnl_44.2.211 |
| PMID | 17850046 |
| OpenAlex | W2152165683 |
| Language | EN |
| Citations received | 6 |
| References cited | 5 |
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
Census · Current Population Survey · Econometrics · Multivariate statistics · Population · Sample (material · Sampling design · Standard error · Statistics · Survey data collection · Computer Science · demographic modeling and climate adaptation · Demography · Food Security and Health in Diverse Populations · Healthcare Policy and Management · Mathematics
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| Citations per year | 0.35 |
|---|---|
| Citation span | 2009 - 2022 (14) |
| Highly cited | No |