Document Detail


Moment Adjusted Imputation for Multivariate Measurement Error Data with Applications to Logistic Regression.
MedLine Citation:
PMID:  24072947     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In clinical studies, covariates are often measured with error due to biological fluctuations, device error and other sources. Summary statistics and regression models that are based on mismeasured data will differ from the corresponding analysis based on the "true" covariate. Statistical analysis can be adjusted for measurement error, however various methods exhibit a tradeo between convenience and performance. Moment Adjusted Imputation (MAI) is method for measurement error in a scalar latent variable that is easy to implement and performs well in a variety of settings. In practice, multiple covariates may be similarly influenced by biological fluctuastions, inducing correlated multivariate measurement error. The extension of MAI to the setting of multivariate latent variables involves unique challenges. Alternative strategies are described, including a computationally feasible option that is shown to perform well.
Authors:
Laine Thomas; Leonard A Stefanski; Marie Davidian
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Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Computational statistics & data analysis     Volume:  67     ISSN:  0167-9473     ISO Abbreviation:  Comput Stat Data Anal     Publication Date:  2013 Nov 
Date Detail:
Created Date:  2013-9-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100960938     Medline TA:  Comput Stat Data Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  15-24     Citation Subset:  -    
Affiliation:
Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27705, U.S.A.
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