A new likelihood model for analyses of pharmacoepidemiologic case–control studies which avoids decision rules for determining latent exposure status

Table 1 Simulation results, data generated with a log-normal backward recurrence density

The datasets had a sample size of 39,600, and on average 80% of patients continue treatment at the index date, 25% of patients have a prescription redemption in the year before the index date and the true OR is 3. For each setting 2,500 datasets were generated and analyzed. \(\mu\) and \(\sigma\) are parameters of the assumed Log-Normal Backward Recurrence Density used for generating data, see text for details
(*) Analysis methods:
1:1 CC indicates 1 control per case, 1:10 CC indicates 10 controls per case
True expo – logistic regression with the actual exposure status as covariate (the reference analysis)
CC WTD – estimation based on joint likelihood for case–control status and the reverse WTD, Log-Normal Backward Recurrence Density
WTD prob – a reverse WTD with Log-Normal Backward Recurrence Density is estimated to predict the probability of an individual being exposed and this exposure probability is used as covariate in logistic regression
90 days – individuals are considered exposed if they have a redemption < 90 days before index date
30 days – individuals are considered exposed if they have a redemption < 30 days before index date, logistic regression

ISSN: 1471-2288