Adaptive thresholding estimator for differential association structures in two independent contingency tables

Abstract

In this paper, we consider an adaptive thresholding procedure to estimate the difference of association structures in two independent two-way contingency tables of the same order. Here, we assume that the class of paired association structures have an approximately sparse difference. Under $L_1$ and $L_2$ loss functions, we establish the corresponding risk's upper bounds for our differential association adaptive thresholding estimators. Moreover, we show that these estimators perform well in a simulated setting. In this line, we carry out a simulation study and compare two well-known independent social mobility datasets.