Literature DB >> 467396

Some insights into Miettinen's multivariate confounder score approach to case-control study analysis.

M C Pike, J Anderson, N Day.   

Abstract

We have studied Miettinen's multivariate confounder score method of controlling confounding in case-control studies both theoretically and by simulation. The main conclusion to be drawn from out results is that the method will in many practical situations seriously exaggerate the statistical significance achieved, and its use is not to be recommended.

Mesh：

Year:  1979        PMID： 467396      PMCID： PMC1060913          DOI： 10.1136/jech.33.1.104

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN： 0143-005X            Impact factor:   3.710


  4 in total

1.  Statistical aspects of the analysis of data from retrospective studies of disease.

Authors:  N MANTEL; W HAENSZEL
Journal:  J Natl Cancer Inst       Date:  1959-04       Impact factor: 13.506

2.  Stratification by a multivariate confounder score.

Authors:  O S Miettinen
Journal:  Am J Epidemiol       Date:  1976-12       Impact factor: 4.897

3.  Multivariate analysis for matched case-control studies.

Authors:  T R Holford; C White; J L Kelsey
Journal:  Am J Epidemiol       Date:  1978-03       Impact factor: 4.897

4.  Are there two logistic regressions for retrospective studies?

Authors:  N Breslow; W Powers
Journal:  Biometrics       Date:  1978-03       Impact factor: 2.571
  4 in total
  12 in total

Review 1.  Indications for propensity scores and review of their use in pharmacoepidemiology.

Authors:  Robert J Glynn; Sebastian Schneeweiss; Til Stürmer
Journal:  Basic Clin Pharmacol Toxicol       Date:  2006-03       Impact factor: 4.080

2.  Evaluating uses of data mining techniques in propensity score estimation: a simulation study.

Authors:  Soko Setoguchi; Sebastian Schneeweiss; M Alan Brookhart; Robert J Glynn; E Francis Cook
Journal:  Pharmacoepidemiol Drug Saf       Date:  2008-06       Impact factor: 2.890

3.  Control for confounding in case-control studies using the stratification score, a retrospective balancing score.

Authors:  Andrew S Allen; Glen A Satten
Journal:  Am J Epidemiol       Date:  2011-03-14       Impact factor: 4.897

4.  Marginal Structural Models for Risk or Prevalence Ratios for a Point Exposure Using a Disease Risk Score.

Authors:  David B Richardson; Alexander P Keil; Alan C Kinlaw; Stephen R Cole
Journal:  Am J Epidemiol       Date:  2019-05-01       Impact factor: 4.897

5.  Evaluation of propensity scores, disease risk scores, and regression in confounder adjustment for the safety of emerging treatment with group sequential monitoring.

Authors:  Stanley Xu; Susan Shetterly; Andrea J Cook; Marsha A Raebel; Sunali Goonesekera; Azadeh Shoaibi; Jason Roy; Bruce Fireman
Journal:  Pharmacoepidemiol Drug Saf       Date:  2016-02-15       Impact factor: 2.890

6.  On the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated: a simulation study.

Authors:  Finbarr P Leacy; Elizabeth A Stuart
Journal:  Stat Med       Date:  2013-10-22       Impact factor: 2.373

7.  Role of disease risk scores in comparative effectiveness research with emerging therapies.

Authors:  Robert J Glynn; Joshua J Gagne; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-05       Impact factor: 2.890

8.  Public health impact of adverse bone effects of oral corticosteroids.

Authors:  T P van Staa; L Abenhaim; C Cooper; B Zhang; H G Leufkens
Journal:  Br J Clin Pharmacol       Date:  2001-06       Impact factor: 4.335

9.  A simple and improved correction for population stratification in case-control studies.

Authors:  Michael P Epstein; Andrew S Allen; Glen A Satten
Journal:  Am J Hum Genet       Date:  2007-03-29       Impact factor: 11.025

Review 10.  Disease risk score as a confounder summary method: systematic review and recommendations.

Authors:  Mina Tadrous; Joshua J Gagne; Til Stürmer; Suzanne M Cadarette
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-11-21       Impact factor: 2.890
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