Literature DB >> 12495160

A note on estimating crude odds ratios in case-control studies with differentially misclassified exposure.

Robert H Lyles1.   

Abstract

Morrissey and Spiegelman (1999, Biometrics 55, 338 344) provided a comparative study of adjustment methods for exposure misclassification in case-control studies equipped with an internal validation sample. In addition to the maximum likelihood (ML) approach, they considered two intuitive procedures based on proposals in the literature. Despite appealing ease of computation associated with the latter two methods, efficiency calculations suggested that ML was often to be recommended for the analyst with access to a numerical routine to facilitate it. Here, a reparameterization of the likelihood reveals that one of the intuitive approaches, the inverse matrix method, is in fact ML under differential misclassification. This correction is intended to alert readers to the existence of a simple closed-form ML estimator for the odds ratio in this setting so that they may avoid assuming that a commercially inaccessible optimization routine must be sought to implement ML.

Entities:  

Mesh:

Year:  2002        PMID: 12495160     DOI: 10.1111/j.0006-341x.2002.1034_1.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  23 in total

1.  A few remarks on "A capture-recapture approach for screening using two diagnostic tests with availability of disease status for the test positives only" by Böhning and Patilea.

Authors:  Haitao Chu; Lei Nie
Journal:  J Am Stat Assoc       Date:  2008-12       Impact factor: 5.033

Review 2.  The effect of misclassification on the estimation of association: a review.

Authors:  Michael Höfler
Journal:  Int J Methods Psychiatr Res       Date:  2005       Impact factor: 4.035

3.  Extended Matrix and Inverse Matrix Methods Utilizing Internal Validation Data When Both Disease and Exposure Status Are Misclassified.

Authors:  Li Tang; Robert H Lyles; Ye Ye; Yungtai Lo; Caroline C King
Journal:  Epidemiol Methods       Date:  2013-09-01

4.  Analysis in case-control sequencing association studies with different sequencing depths.

Authors:  Sixing Chen; Xihong Lin
Journal:  Biostatistics       Date:  2020-07-01       Impact factor: 5.899

5.  Validation data-based adjustments for outcome misclassification in logistic regression: an illustration.

Authors:  Robert H Lyles; Li Tang; Hillary M Superak; Caroline C King; David D Celentano; Yungtai Lo; Jack D Sobel
Journal:  Epidemiology       Date:  2011-07       Impact factor: 4.822

6.  An augmented estimation procedure for EHR-based association studies accounting for differential misclassification.

Authors:  Jiayi Tong; Jing Huang; Jessica Chubak; Xuan Wang; Jason H Moore; Rebecca A Hubbard; Yong Chen
Journal:  J Am Med Inform Assoc       Date:  2020-02-01       Impact factor: 4.497

7.  On the estimation of disease prevalence by latent class models for screening studies using two screening tests with categorical disease status verified in test positives only.

Authors:  Haitao Chu; Yijie Zhou; Stephen R Cole; Joseph G Ibrahim
Journal:  Stat Med       Date:  2010-05-20       Impact factor: 2.373

8.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.

Authors:  Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Ruth H Keogh; Victor Kipnis; Janet A Tooze; Michael P Wallace; Helmut Küchenhoff; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

9.  Methods to adjust for misclassification in the quantiles for the generalized linear model with measurement error in continuous exposures.

Authors:  Ching-Yun Wang; Jean De Dieu Tapsoba; Catherine Duggan; Kristin L Campbell; Anne McTiernan
Journal:  Stat Med       Date:  2015-11-22       Impact factor: 2.373

10.  A Bayesian approach for correcting exposure misclassification in meta-analysis.

Authors:  Qinshu Lian; James S Hodges; Richard MacLehose; Haitao Chu
Journal:  Stat Med       Date:  2018-09-24       Impact factor: 2.373

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.