We have been developing a two-part general guidance document for biostatisticians on dealing with measurement error and misclassification. The document includes explanations regarding errors in explanatory variables versus outcome variables in regression analyses, classical and linear measurement error versus Berkson error and misclassification of categorical variables. It points to options for statistical methods and software that has been developed to allow analyses that adjust for such error and misclassification. Moreover, different kinds of ancillary studies are explained, which are used to specify and estimate the measurement error model.
"STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology:
Part 2 – more complex methods of adjustment and advanced topics"
Statistics in Medicine, Link