Hi all,
i want to do multiple imputation on iem level, since several studies have shown the superiority of item level imputation compared to scale level.
I want to do a sensitivity analysis. Some authors suggest, to add or substract a constant to the imputed values. However many of the applications used continious scale scores for such analysis. Since I do imputation on item level, I could add such a constant, however, I have never seen any comparable application. I know many of NMAR models (selection models and so on), however, since I am not interested in growth, they do not fit my application (at least I think so).
So, du you think this strategy is reasonable and do you have any papers, that have used this strategy. Or any other suggestions?
Many thanks in advance,
best wishes, Manuel
Try:
Goldstein, Bonnet and Rocher (2007) Multilevel Structural Equation Models for the Analysis of Comparative Data on Educational PerformanceJournal of Educational and Behavioral Statistics Vol. 32, No. 3, pp. 252–286
http://jeb.sagepub.com/content/32/3/252.full.pdf+html
AND
Lin (2006) Missing Data Imputation in Quality-of-Life Assessment
PharmacoEconomics Volume 24, Issue 9, pp 917–925
Dear Manuel,
see if the doc in attch helps you.
good luck with your research!
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