ISSN:
0081-1750
Language:
English
Titel der Quelle:
Sociological methodology : an official publication of the American Sociological Association
Publ. der Quelle:
Thousand Oaks, Calif : Sage Publications
Angaben zur Quelle:
Vol. 37, No. 1 (2007), p. 83-117
DDC:
300
Abstract:
When fitting a generalized linear model--such as linear regression, logistic regression, or hierarchical linear modeling--analysts often wonder how to handle missing values of the dependent variable Y. If missing values have been filled in using multiple imputation, the usual advice is to use the imputed Y values in analysis. We show, however, that using imputed Ys can add needless noise to the estimates. Better estimates can usually be obtained using a modified strategy that we call multiple imputation, then deletion (MID). Under MID, all cases are used for imputation but, following imputation, cases with imputed Y values are excluded from the analysis. When there is something wrong with the imputed Y values, MID protects the estimates from the problematic imputations. And when the imputed Y values are acceptable, MID usually offers somewhat more efficient estimates than an ordinary MI strategy.
Note:
Copyright: © Copyright 2007 American Sociological Association
,
Copyright: © COPYRIGHT 2007 Blackwell Publishers Ltd.
DOI:
10.1111/j.1467-9531.2007.00180.x
URL:
http://www.jstor.org/stable/20451132
URL:
http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9531.2007.00180.x/abstract
URL:
http://search.proquest.com/docview/216125965
URL:
http://arxiv.org/abs/1605.01095
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