1 / 15

A Comparison of Two Sample Designs for the MEPS-IC

A Comparison of Two Sample Designs for the MEPS-IC. John P. Sommers Agency for Healthcare Research and Quality Anne T. Kearney U. S. Census Bureau. Presentation Outline. What is the MEPS-IC? The Two Private Sector Sample Designs Purpose of this Study Measures Used to Compare Results

elliot
Download Presentation

A Comparison of Two Sample Designs for the MEPS-IC

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. A Comparison of Two Sample Designs for the MEPS-IC John P. Sommers Agency for Healthcare Research and Quality Anne T. Kearney U. S. Census Bureau

  2. Presentation Outline • What is the MEPS-IC? • The Two Private Sector Sample Designs • Purpose of this Study • Measures Used to Compare • Results • Lessons Learned

  3. The Medical Expenditure Panel Survey - Insurance Component (MEPS-IC) • Annual survey of Business Establishments and Governments • Information Collected on Offer Rates, Enrollments, Costs and Characteristics of Employer Health Insurance

  4. 14 strata per state Strata boundaries are employment size classes Min sample in 40 states 31 largest states have minimum each year Average state variance components Optimal allocation using 2 variables 15 strata per state Strata boundaries are predicted: % offering and # enrollees Min sample in all states Average state variance components Optimal allocation using 3 variables Comparison of Old and New DesignsOLDNEW

  5. Purpose of this Study • To determine if the new sample design fully implemented in 2004 improved our estimates of variances for eight key variables of interest.

  6. Problem: How to Evaluate and Compare Sample Designs Across Years, 2002 vs. 2004 • Could not compare standard errors due to the natural increase in some standard errors as mean values increase • Changes in sample allocation to states: • 2002 had fewer sample units • 2002 did not have min sample sizes in all states

  7. Quality MeasuresInitial Step • We did comparisons over the 31 largest states since they had similar sample size before nonresponse in both years • These 31 largest states have over 90% of universe • We created pseudo-national level estimates from these 31 states

  8. Quality Measures • Relative Standard Error (RSE) • Square Root of the Design Effect • Unit RSE = Square root of sample size times RSE

  9. Tested Hypothesis

  10. Pseudo National Estimates

  11. Average Results of State Estimates

  12. Average National Results by Firm Size

  13. Average National Results by Industry

  14. Lessons Learned • Targeted and most other estimates improved at the State and National Level • Effect of new sample design on estimates for subpopulations appears to depend upon the prevalence within the subcategory of offering insurance to employees

  15. John.Sommers@ahrq.hhs.govAnne.Theresa.Kearney@census.gov

More Related