A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies.

ABSTRACT:

Background

Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.

Methods

We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure depende

SUBMITTER: Kubota K 

PROVIDER: S-EPMC8520620 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature