We propose the use of an improved sandwich estimator that has the ability to produce unbiased estimates of variances and covariances in studies of correlated data with rare event and small sample sizes. Our approach will be to adjust the sandwich estimator to compensate for underestimation in these situations. In general, this adjustment is performed by taking an alternate sandwich estimator, developed by Pan, and improving its performance in small sample size and rare event settings by adding an appropriate inflation factor, while still preserving the asymptotic nature of the sandwich estimator. The performance of this improved sandwich estimator will be evaluated with simulated and real-world data sets.
