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

Autor/inn/en	Joe, Harry; Maydeu-Olivares, Alberto
Titel	A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data
Quelle	In: Psychometrika, 75 (2010) 3, S.393-419 (27 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-010-9165-5
Schlagwörter	Statistical Analysis; Information Theory; Data Analysis; Item Response Theory; Goodness of Fit + Suchen Sie Ihr Suchwort? Statistische Analyse; Informationstheorie; Auswertung; Item-Response-Theorie
Abstract	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[squared]" 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. (As Provided).
Anmerkungen	Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10