Identification of Multiple Outlying Cells in Multi-way Tables

Abstract

An identification method is proposed in order to detect more than one outlying cells in multi-way contingency tables. The iterative proportional fitting method is applied to get expected values of several suspected outlying cells. Since the proposed method uses minimal sufficient statistics under quasi log-linear models, expected counts of outlying cells could be estimated under any hierarchical log-linear models. This method is an extension of the backwards-stepping method of Simonoff(1988) and requires les iteration to identify outlying cells.

Keywords

• backwards-stepping;
• Bonfferoni bound;
• deleted residual;
• influence;
• masking effect;
• minimal sufficient statistics;
• outlying cell;
• quasi-independent;
• wamping effect

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References

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