Measurement error, instrumental variables and corrections for attenuation with applications to meta-analyses.
MacMahon et al. present a meta-analysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already existing in the literature, as well as to a new instrumental variable method. The assumptions justifying the various methods are examined and their efficiencies are studied via simulation. Compared to the methods we discuss, the method of MacMahon et al. may have bias in some circumstances because it does not take into account: (i) possible correlations among the predictors within a study; (ii) possible bias in the second measurement; or (iii) possibly differing marginal distributions of the predictors or measurement errors across studies. A unifying asymptotic theory using estimating equations is also presented.
Department of Statistics, Texas A&M University, College Station 77843.
R J
RJ
Carroll
L A
LA
Stefanski
D015982:Bias; D001794:Blood Pressure; D002561:Cerebrovascular Disorders / Q000453:epidemiology / Q000209:etiology; D003327:Coronary Disease / Q000453:epidemiology / Q000209:etiology; D003627:Data Interpretation, Statistical; D006801:Humans; D016015:Logistic Models; D015201:Meta-Analysis as Topic; D012044:Regression Analysis; D012307:Risk Factors