Back to search

Article

Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification

2019-12-30

Abstract excerpt

Health research using electronic health records (EHR) has gained popularity, but misclassification of EHR-derived disease status and lack of representativeness of the study sample can result in substantial bias in effect estimates and can impact power and type I error. In this paper, we develop new strategies for handling disease status misclassification and selection bias in EHR-based association studies. We firs...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
29dcbd8c-6fc6-59c5-b6f1-766d02618bf8
DOI
10.1101/2019.12.26.19015859
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassificationDOI 10.1101/2019.12.26.19015859
Select a neighboring publication to make it the new centre.