A Unified Approach to Measurement Error and Missing Data: Overview and Applications

Autor/inn/en	Blackwell, Matthew; Honaker, James; King, Gary
Titel	A Unified Approach to Measurement Error and Missing Data: Overview and Applications
Quelle	In: Sociological Methods & Research, 46 (2017) 3, S.303-341 (39 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
DOI	10.1177/0049124115585360
Schlagwörter	Error of Measurement; Monte Carlo Methods; Data Collection; Simulation; Probability; Computation; Social Sciences; Social Scientists; Statistical Inference; Multivariate Analysis; Research Problems; Data Interpretation + Suchen Sie Ihr Suchwort? Messfehler; Monte-Carlo-Methode; Data capture; Datensammlung; Simulation program; Simulationsprogramm; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Social scientist; Sozialwissenschaftler; Inferential statistics; Schließende Statistik; Multivariate Analyse; Forschungskritik; Data evaluation; Datenauswertung
Abstract	Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model dependence, difficult computation, or inapplicability with multiple mismeasured variables. We develop an easy-to-use alternative without these problems; it generalizes the popular multiple imputation (MI) framework by treating missing data problems as a limiting special case of extreme measurement error and corrects for both. Like MI, the proposed framework is a simple two-step procedure, so that in the second step researchers can use whatever statistical method they would have if there had been no problem in the first place. We also offer empirical illustrations, open source software that implements all the methods described herein, and a companion article with technical details and extensions. [For the companion article, "A Unified Approach to Measurement Error and Missing Data: Details and Extensions," see EJ1148104.] (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01