A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data

作者：Joe Harry; Maydeu Olivares Alberto^*

来源：Psychometrika, 2010, 75(3): 393-419.

DOI：10.1007/s11336-010-9165-5

• categorical data analysis
• cell-focusing
• discrete data
• item response theory
• overdispersion
• overlapping cells
• Poisson models
• quadratic form statistics
• Rasch models
• score test
• sparse contingency tables
• zero-inflation

Maydeu-Olivares and Joe (J. Am. Stat. Assoc. 100:1009-1020, 2005; Psychometrika 71:713-732, 2006) introduced classes of chi-square tests for (sparse) multidimensional multinomial data based on low-order marginal proportions. Our extension provides general conditions under which quadratic forms in linear functions of cell residuals are asymptotically chi-square. The new statistics need not be based on margins, and can be used for one-dimensional multinomials. We also provide theory that explains why limited information statistics have good power, regardless of sparseness. We show how quadratic-form statistics can be constructed that are more powerful than X (2) and yet, have approximate chi-square null distribution in finite samples with large models. Examples with models for truncated count data and binary item response data are used to illustrate the theory.

• 出版日期2010-9