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Estimation of Non-Response Bias in the Medicare FFS HOS

We examined non-response bias in physical component summary scores (PCS) and mental component summary scores (MCS) in the Medicare fee-for-service (FFS) Health Outcomes Survey (HOS) using two alternative methods, response propensity weighting and imputation for non-respondents. The two approaches ga...

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Autores principales: McCall, Nancy, Khatutsky, Galina, Smith, Kevin, Pope, Gregory C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: CENTERS for MEDICARE & MEDICAID SERVICES 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194889/
https://www.ncbi.nlm.nih.gov/pubmed/15493442
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author McCall, Nancy
Khatutsky, Galina
Smith, Kevin
Pope, Gregory C.
author_facet McCall, Nancy
Khatutsky, Galina
Smith, Kevin
Pope, Gregory C.
author_sort McCall, Nancy
collection PubMed
description We examined non-response bias in physical component summary scores (PCS) and mental component summary scores (MCS) in the Medicare fee-for-service (FFS) Health Outcomes Survey (HOS) using two alternative methods, response propensity weighting and imputation for non-respondents. The two approaches gave nearly identical estimates of non-response bias. PCS scores were 0.74 points lower and MCS scores 0.51 points lower after adjustment for non-response through imputation and 0.63 and 0.46 lower after adjustment for propensity weighting. These levels are small for component scores suggesting that survey non-response to the FFS HOS does not adversely affect estimates of average health status for this population.
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spelling pubmed-41948892014-11-04 Estimation of Non-Response Bias in the Medicare FFS HOS McCall, Nancy Khatutsky, Galina Smith, Kevin Pope, Gregory C. Health Care Financ Rev Research Article We examined non-response bias in physical component summary scores (PCS) and mental component summary scores (MCS) in the Medicare fee-for-service (FFS) Health Outcomes Survey (HOS) using two alternative methods, response propensity weighting and imputation for non-respondents. The two approaches gave nearly identical estimates of non-response bias. PCS scores were 0.74 points lower and MCS scores 0.51 points lower after adjustment for non-response through imputation and 0.63 and 0.46 lower after adjustment for propensity weighting. These levels are small for component scores suggesting that survey non-response to the FFS HOS does not adversely affect estimates of average health status for this population. CENTERS for MEDICARE & MEDICAID SERVICES 2004 /pmc/articles/PMC4194889/ /pubmed/15493442 Text en
spellingShingle Research Article
McCall, Nancy
Khatutsky, Galina
Smith, Kevin
Pope, Gregory C.
Estimation of Non-Response Bias in the Medicare FFS HOS
title Estimation of Non-Response Bias in the Medicare FFS HOS
title_full Estimation of Non-Response Bias in the Medicare FFS HOS
title_fullStr Estimation of Non-Response Bias in the Medicare FFS HOS
title_full_unstemmed Estimation of Non-Response Bias in the Medicare FFS HOS
title_short Estimation of Non-Response Bias in the Medicare FFS HOS
title_sort estimation of non-response bias in the medicare ffs hos
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194889/
https://www.ncbi.nlm.nih.gov/pubmed/15493442
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