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Autor/inn/enAßmann, Christian; Würbach, Ariane; Goßmann, Solange; Geissler, Ferdinand; Bela, Anika
TitelNonparametric Multiple Imputation for Questionnaires with Individual Skip Patterns and Constraints: The Case of Income Imputation in The National Educational Panel Study
QuelleIn: Sociological Methods & Research, 46 (2017) 4, S.864-897 (34 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0049-1241
DOI10.1177/0049124115610346
SchlagwörterNonparametric Statistics; Questionnaires; Statistical Analysis; National Surveys; Income; Response Style (Tests); Classification; Regression (Statistics); Foreign Countries; Adults; Cohort Analysis; Germany
AbstractLarge-scale surveys typically exhibit data structures characterized by rich mutual dependencies between surveyed variables and individual-specific skip patterns. Despite high efforts in fieldwork and questionnaire design, missing values inevitably occur. One approach for handling missing values is to provide multiply imputed data sets, thus enhancing the analytical potential of the surveyed data. To preserve possible nonlinear relationships among variables and incorporate skip patterns that make the full conditional distributions individual specific, we adapt a full conditional multiple imputation approach based on sequential classification and regression trees. Individual-specific skip patterns and constraints are handled within imputation in a way ensuring the consistency of the sequence of full conditional distributions. The suggested approach is illustrated in the context of income imputation in the adult cohort of the National Educational Panel Study. (As Provided).
AnmerkungenSAGE 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 vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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