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Abstract Details

Activity Number: 142
Type: Contributed
Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Survey Research Methods
Abstract - #308783
Title: Statistical Graphics of Pearson Residuals in Survey Logistic Regression Diagnosis
Author(s): Stanley S. Weng*+
Companies: National Agricultural Statistics Service
Address: 3251 Old Lee Hwy., Fairfax, VA, 20136,
Keywords: Pearson residuals normality graph ; Statistical graphical modeling

For survey data logistic regression, the model fitness has been assessed through a set of diagnostic statistics, borrowed from the logistic regression in generalized linear models. However, for survey data, these statistics may need to be reexamined. In practice, we have observed their irregular behaviors, which make their established statistical criterion suspect. This presentation reports our use of Pearson residuals normality graphs as graphical diagnostic statistics, to assess survey data logistic modeling, as in a recent NASS study. Statistical graphics summary may provide broader scope and more elaborated information than analytical summary. The statistical graphs of Pearson residuals showed their diagnostic ability, and their careful reading may reveal delicate diagnostic information on modeling effects. We illustrate the statistical graphical modeling process with our analysis.

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