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Statistica Sinica 28 (2018), 1887-1905

ASSESSMENT OF NONIGNORALBE LOG-LINEAR
MODELS FOR AN INCOMPLETE CONTINGENCY TABLE
Seongyong Kim and Daeyoung Kim
Hoseo University and University of Massachusetts, Amherst

Abstract: A challenging problem in the analysis of an incomplete contingency table is that the use of nonignorable nonresponse models requires explicit specification of missing data mechanism. In this paper we propose a data analytic approach to aid in distinguishing between plausible nonignorable log-linear models for an incomplete contingency table. The proposed method involves the computation of a set of response odds and nonresponse odds that are directly connected with the magnitude of the parameters representing types of nonignorable mechanism assumed in the log-linear models. These odds can be easily estimated from observed counts. We illustrate the performance of the proposed method with simulation and data. We also discuss a generalizability of the proposed method in two directions, its applicability for a three-way incomplete contingency table and its applicability for nonignorable nonresponse models other than the log-linear models.

Key words and phrases: Contingency table, log-linear model, nonignorable nonresponse.

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