The investigation and correction of recall bias for an ordinal response in a case‐control study

Abstract

Consider a case-control study designed to investigate the possible association between development of a particular disease and the value of a putative risk factor measured on an ordinal scale. Let E denote a subject's true risk factor value and let E* denote a subject's recorded risk factor value. Misclassification bias occurs if conclusions reached regarding the relationship between disease status and E* do not also apply to the relationship between disease status and E. We propose a model for the conditional probability distribution of E* given E. We show how the model may be used to investigate misclassification bias in a validation study where measurements of E* and E are available for both cases and controls and apply the methods developed to data from a test-retest study of recall bias in the context of screening for hypertension. We also consider a situation where the validation study is carried out on a subset of the subjects within a larger case-control study. In that case, values for E* are available for all subjects but values for E are available only for those subjects included in the validation study. We show how correct likelihood-based inference concerning association between disease status and risk factor value may be carried out using all of the available data. A Monte Carlo study shows how the inclusion of a validation study leads to a correction of recall bias problems at the cost of an increased standard error for the estimated association parameter.