American Journal of Epidemiology · 2012 · 297 citations · 24 references
Statistical FoundationGenetic EpidemiologyAnthropometric IndicatorMathematical StatisticProspective Cohort StudyObesityMetabolic SyndromeBody CompositionInstrumental Variable AssumptionsRandomized Controlled TrialBiostatisticsPublic HealthStatisticsPsychiatryIv AssumptionsEpidemiologyMendelian RandomizationEconometricsStatistical InferenceIv AssessmentsMedicine
Mendelian randomization studies rely on strong instrumental variable assumptions that are rarely systematically evaluated, and while such evaluation could enhance credibility, the approaches are not fail‑safe and may miss bias or incorrectly flag valid instruments. The authors aim to present methods for assessing the validity of MR studies and to describe the assumptions underlying these assessments. They describe and apply a set of methods to an MR study using the FTO genotype to estimate obesity’s effect on mental disorder, noting that the methods are applicable to any IV analysis regardless of source. The methods applied to the FTO study are generally inconclusive, but routine application is likely to improve the scientific contributions of MR studies.
As with other instrumental variable (IV) analyses, Mendelian randomization (MR) studies rest on strong assumptions. These assumptions are not routinely systematically evaluated in MR applications, although such evaluation could add to the credibility of MR analyses. In this article, the authors present several methods that are useful for evaluating the validity of an MR study. They apply these methods to a recent MR study that used fat mass and obesity-associated (FTO) genotype as an IV to estimate the effect of obesity on mental disorder. These approaches to evaluating assumptions for valid IV analyses are not fail-safe, in that there are situations where the approaches might either fail to identify a biased IV or inappropriately suggest that a valid IV is biased. Therefore, the authors describe the assumptions upon which the IV assessments rely. The methods they describe are relevant to any IV analysis, regardless of whether it is based on a genetic IV or other possible sources of exogenous variation. Methods that assess the IV assumptions are generally not conclusive, but routinely applying such methods is nonetheless likely to improve the scientific contributions of MR studies.
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Specification Tests in Econometrics
Jerry A. Hausman · Econometrica · 1978 · 18K citations
Applied Economics, Time Series Econometrics, Instrumental Variable Test +17