Bias reduction for risk ratio and vaccine effect estimators

Bias reduction for risk ratio and vaccine effect estimators.

We examine the structural bias for established estimators of vaccine effects on susceptibility and for newer estimates of vaccine effects on infectiousness. We then propose and analyse new bias corrections for vaccine effect estimators of both susceptibility and infectiousness, as well as their combined effect on infection transmission. Each estimator is evaluated empirically with computer simu...

Bias Reduction for Bayesian and Frequentist Estimators

We show that in parametric likelihood models the first order bias in the posterior mode and the posterior mean can be removed using objective Bayesian priors. These bias-reducing priors are defined as the solution to a set of differential equations which may not be available in closed form. We provide a simple and tractable data dependent prior that solves the differential equations asymptotica...

Bias Reduction and Elimination with Kernel Estimators

with Kernel Estimators Stephan R. Sain1 De ember 8, 2000 SUMMARY: A great deal of resear h has fo used on improving the bias properties of kernel estimators. One proposal involves removing the restri tion of non-negativity on the kernel to onstru t \higher-order" kernels that eliminate additional terms in the Taylor's series expansion of the bias. This paper onsiders an alternative that uses a ...

nonresponse bias reduction by calibration estimators in panel studies

in many statistical systems, a type of survey called “sampling over time” is common, which repeats continuously over time. one method of sampling over time is panel survey. panel survey is a method in which a “fixed sample” is contacted during different waves. the most important challenge in a panel survey is debility in providing response from some sample units and having non-response that usu...

Simple Adjustments to Reduce Bias and Mean Squared Error Associated With Regression-Based Odds Ratio and Relative Risk Estimators