checks for misclassification to improve the quality of the variable. The developed correction procedure is applied to simple …

Abstract The problem of misclassification is common in epidemiological and clinical research. In some cases …, misclassification may be incurred when measuring both exposure and outcome variables. It is well known that validity of analytic results … elucidate extensions of well-studied methods in order to facilitate misclassification adjustment when a binary outcome and …

through an intermediate variable. When the exposure is subject to misclassification, the effects estimated can be severely … estimates in the presence of conditional non-differential misclassification of a binary exposure. We show that in the absence of … interaction, the misclassification of the exposure will bias the direct effect towards the null but can bias the indirect effect …

Most epidemiological studies suffer from misclassification in the response and/or the covariates. Since ignoring … misclassification induces bias on the parameter estimates, correction for such errors is important. For measurement error, the … continuous analog to misclassification, a general approach for bias correction is the SIMEX (simulation extrapolation) originally …

21% of non-repeaters are below grade, while 12% of repeaters are not. Misclassification attenuates regression …

substantially underestimate the true levels of unemployment, due to misclassification errors in labor force status in Current … Population Surveys. Our closed-form identification of the misclassification probabilities relies on the key assumptions that the …