Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates.

Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Research Abstract Details 

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Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Abstract Text:

C Y Wang,Shen-Ming Lee,Edward C Chao,

Imputation, weighting, direct likelihood, and direct Bayesian inference (Rubin, 1976) are important approaches for missing data regression. Many useful semiparametric estimators have been developed for regression analysis of data with missing covariates or outcomes. It has been established that some semiparametric estimators are asymptotically equivalent, but it has not been shown that many are numerically the same. We applied some existing methods to a bladder cancer case-control study and noted that they were the same numerically when the observed covariates and outcomes are categorical. To understand the analytical background of this finding, we further show that when observed covariates and outcomes are categorical, some estimators are not only asymptotically equivalent but also actually numerically identical. That is, although their estimating equations are different, they lead numerically to exactly the same root. This includes a simple weighted estimator, an augmented weighted estimator, and a mean-score estimator. The numerical equivalence may elucidate the relationship between imputing scores and weighted estimation procedures.

Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Publishing Authors By Initials

CY Wang,SM Lee,EC Chao,

For similar geographic locations: americas: north america: united states: northwestern united states: washington research abstracts see: geographic locations: americas: north america: united states: northwestern united states: washington research

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Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Biostatistics (Oxford, England)

VOLUME: 8

Page Numbers: 468-73

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ISSN: 1465-4644

DAY: 12

MONTH: 09

YEAR: 2006

Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Information

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LANGUAGE: eng

NlmUniqueID: 100897327

Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates. Keywords Mesh Terms:

KEYWORDS: Washington

MESH TERMS: etiology

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Grant and Affiliation Information for Numerical equivalence of imputing scores and weighted estimators in regression analysis with missing covariates.

AFFILIATION: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA. cywang@fhcrc.org

Country: England

AGENCY: United States NCI

GRANT: CA88754

ACRONYM: CA

MEDLINETA: Biostatistics

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