Title: |
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Class Variables for MEPS Expenditure Imputations |
Description: |
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The Medical Expenditure Panel Survey (MEPS) collects data on health care utilization, expenditures, sources of payment, insurance coverage, and health care quality measures. The survey was designed to produce national and regional estimates for the U.S. civilian noninstitutionalized population. The data on medical expenses are collected from both household respondents in the Household Component and from a sample of their health care providers in the Medical Provider Component. In the absence of payment information from either component, expenditure data are derived for sample persons through an imputation process. Missing expense data are imputed at the event level for each medical event type using a weighted hot-deck procedure. This process utilizes individual- and event-level data collected in MEPS that are correlated with medical expenditures. Bivariate analyses and linear regression models were utilized to assess the current class variables used for imputation. This paper details the methodology used to select, prioritize, and categorize the class variables used to impute missing expenditures for two event types: doctor visits and inpatients hospitalizations. (Previously published as Working Paper #4005, December 2004.) |
Author(s): |
|
Marc W. Zodet, Diana Z. Wobus, Steven R. Machlin, David Kashihara, Deborah D. Dougherty |
Agency: |
|
Rockville (MD): Agency for Healthcare Research and Quality |
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