Examining the Missing Completely at Random Mechanism in Incomplete Data Sets: A Multiple Testing Approach

Autor/inn/en	Raykov, Tenko; Lichtenberg, Peter A.; Paulson, Daniel
Titel	Examining the Missing Completely at Random Mechanism in Incomplete Data Sets: A Multiple Testing Approach
Quelle	In: Structural Equation Modeling: A Multidisciplinary Journal, 19 (2012) 3, S.399-408 (10 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1070-5511
DOI	10.1080/10705511.2012.687660
Schlagwörter	Data; Data Analysis; Older Adults; Intelligence Tests; Behavioral Science Research; Social Science Research; Raven Advanced Progressive Matrices + Suchen Sie Ihr Suchwort? Daten; Auswertung; Älterer Erwachsener; Intelligence test; Intelligenztest; Social scientific research; Sozialwissenschaftliche Forschung
Abstract	A multiple testing procedure for examining implications of the missing completely at random (MCAR) mechanism in incomplete data sets is discussed. The approach uses the false discovery rate concept and is concerned with testing group differences on a set of variables. The method can be used for ascertaining violations of MCAR and disproving this mechanism in empirical behavioral and social research. The procedure can also be employed when locating violations of MCAR in observed measures is of interest. The outlined approach is illustrated with data from a cognitive intervention study. (Contains 2 tables and 2 footnotes.) (As Provided).
Anmerkungen	Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10