Comparison of Different Filters in Detection of Weak Signals for Large Size Contingency Tables
Comparison of Different Filters in Detection of Weak Signals for Large Size Contingency Tables
Valerii Fedorov, Xiwu Lin, and Rita Patwardhan
Abstract: Detection of weak signals for large size contingency tables is a common task arising from post marketing drug adverse event detection. By using different measures of the strength for the potential signals, different filters may be developed. Traditional statistical methods such as PRR and chi-squared methods targeting the association in contingency tables have been used in such context. Recently a few methods based on Bayesian ideas have been proposed and applied in such kind of application. In this work, we perform statistical comparison of these different methods and investigate the relationships among these different methods. Motivated by the existing methods, we propose a generalized approach which comprises all the discussed methods as its particular cases and offers a way for constructing various alternatives.
