Accounting for Misclassification in Electronic Health Records-derived Exposures Using Generalized Linear Finite Mixture Models

Exposures derived from EHRs may be misclassified, leading to biased estimates of their association with outcomes of interest: finite mixture models can correct biases with no loss of efficiency.
Source: RAND Research Health and Health Care - Category: Health Management Authors: Source Type: research