| Parametric and semiparametric model-based estimates of the finite population mean for two-stage cluster samples with item nonresponse. | |
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MedLine Citation:
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PMID: 17489967 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This article concerns item nonresponse adjustment for two-stage cluster samples. Specifically, we focus on two types of nonignorable nonresponse: nonresponse depending on covariates and underlying cluster characteristics, and depending on covariates and the missing outcome. In these circumstances, standard weighting and imputation adjustments are liable to be biased. To obtain consistent estimates, we extend the standard random-effects model by modeling these two types of missing data mechanism. We also propose semiparametric approaches based on fitting a spline on the propensity score, to weaken assumptions about the relationship between the outcome and covariates. These new methods are compared with existing approaches by simulation. The National Health and Nutrition Examination Survey data are used to illustrate these approaches. |
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Authors:
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Ying Yuan; Roderick J A Little |
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Publication Detail:
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Type: Journal Article Date: 2007-05-08 |
Journal Detail:
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Title: Biometrics Volume: 63 ISSN: 0006-341X ISO Abbreviation: Biometrics Publication Date: 2007 Dec |
Date Detail:
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Created Date: 2007-12-14 Completed Date: 2008-01-22 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0370625 Medline TA: Biometrics Country: United States |
Other Details:
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Languages: eng Pagination: 1172-80 Citation Subset: IM |
Affiliation:
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Department of Biostatistics and Applied Mathematics, M.D. Anderson Cancer Center, Houston, Texas 77030, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Cluster Analysis* Computer Simulation Data Collection Data Interpretation, Statistical* Demography* Models, Biological* Models, Statistical* Reproducibility of Results Sample Size Sensitivity and Specificity |
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