Imputing Missing Data: A Comparison of Methods for Social Work Researchers

Autor/inn/en	Saunders, Jeanne A.; Morrow-Howell, Nancy; Spitznagel, Edward; Dore, Peter; Proctor, Enola K.; Pescarino, Richard
Titel	Imputing Missing Data: A Comparison of Methods for Social Work Researchers
Quelle	In: Social Work Research, 30 (2006) 1, S.19-31 (13 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1070-5309
Schlagwörter	Social Work; Decision Making; Social Science Research; Multivariate Analysis; Formative Evaluation; Error Correction; Data Analysis; Methods Research; Program Evaluation; Comparative Analysis + Suchen Sie Ihr Suchwort? Soziale Arbeit; Decision-making; Entscheidungsfindung; Social scientific research; Sozialwissenschaftliche Forschung; Multivariate Analyse; Korrektur; Auswertung; Methodenforschung; Programme evaluation; Programmevaluation
Abstract	Choosing the most appropriate method to handle missing data during analyses is one of the most challenging decisions confronting researchers. Often, missing values are just ignored rather than replaced with a reliable imputation method. Six methods of data imputation were used to replace missing data from two data sets of varying sizes; this article examines the results. Each imputation method is defined, and the pros and cons of its use in social science research are identified. The authors discuss comparisons of descriptive measures and multivariate analyses with the imputed variables and the results of a timed study to determine how long it took to use each imputation method on first and subsequent use. Implications for social work research are suggested. (Author).
Anmerkungen	National Association of Social Workers (NASW). 750 First Street NE Suite 700, Washington, DC 20002. Tel: 800-227-3590; E-mail: press@naswdc.org; Web site: http://www.naswpress.org.
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10