Document Detail

Simulation study of hierarchical regression.
MedLine Citation:
PMID:  8804145     Owner:  NLM     Status:  MEDLINE    
Hierarchical regression - which attempts to improve standard regression estimates by adding a second-stage 'prior' regression to an ordinary model - provides a practical approach to evaluating multiple exposures. We present here a simulation study of logistic regression in which we compare hierarchical regression fitted by a two-stage procedure to ordinary maximum likelihood. The simulations were based on case-control data on diet and breast cancer, where the hierarchical model uses a second-stage regression to pull conventional dietary-item estimates toward each other when they have similar levels of food constituents. Our results indicate that hierarchical modelling of continuous covariates offers worthwhile improvement over ordinary maximum-likelihood, provided one does not underspecify the second-stage standard deviations.
J S Witte; S Greenland
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Statistics in medicine     Volume:  15     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  1996 Jun 
Date Detail:
Created Date:  1996-11-19     Completed Date:  1996-11-19     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  1161-70     Citation Subset:  IM    
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44109-1998, USA.
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MeSH Terms
Bayes Theorem
Breast Neoplasms / diet therapy
Case-Control Studies
Confidence Intervals
Least-Squares Analysis
Likelihood Functions
Models, Statistical*
Regression Analysis*
Research Design
Grant Support

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