2021
Testing gene–environment interactions in the presence of confounders and mismeasured environmental exposures
Cheng C, Spiegelman D, Wang Z, Wang M. Testing gene–environment interactions in the presence of confounders and mismeasured environmental exposures. G3: Genes, Genomes, Genetics 2021, 11: jkab236. PMID: 34568916, PMCID: PMC8473983, DOI: 10.1093/g3journal/jkab236.Peer-Reviewed Original ResearchConceptsStandard logistic regression approachGreater statistical powerStatistical powerBinary disease outcomeComputational efficiencyIllustrative exampleComputation timeExtensive simulation experimentsMost simulation scenariosMeasurement errorRegression approachConsideration adjustmentsSimulation experimentsExposure measurement errorReverse testLogistic regression approachSimulation scenariosLinear discriminant analysisApproachReverse approachPowerErrorDiscriminant analysis
1999
Evaluation of Old and New Tests of Heterogeneity in Epidemiologic Meta-Analysis
Takkouche B, Cadarso-Suárez C, Spiegelman D. Evaluation of Old and New Tests of Heterogeneity in Epidemiologic Meta-Analysis. American Journal Of Epidemiology 1999, 150: 206-215. PMID: 10412966, DOI: 10.1093/oxfordjournals.aje.a009981.Peer-Reviewed Original ResearchConceptsParametric bootstrap versionBootstrap versionLarge simulation studyCorrect type IStatistical powerComputational easeSimulation studyIdentification of heterogeneityHypothesis testQ statisticStudy varianceLow statistical powerNull hypothesisStatisticsPoint of viewBootstrapHomogeneity testVersionPowerDecision criteriaNew testBest choiceKey featuresEffect measuresVariance