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Sensitivity Analysis of Multiple Informant Models When Data Are Not Missing at Random

โœ Scribed by Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Scaramella, Laura V.; Leve, Leslie D.; Reiss, David


Book ID
120326903
Publisher
Lawrence Erlbaum Associates, Inc.
Year
2013
Tongue
English
Weight
264 KB
Volume
20
Category
Article
ISSN
1070-5511

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On summary measures analysis of the line
โœ Roderick J. Little; Trivellore Raghunathan ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 139 KB ๐Ÿ‘ 2 views

Subjects often drop out of longitudinal studies prematurely, yielding unbalanced data with unequal numbers of measures for each subject. A simple and convenient approach to analysis is to develop summary measures for each individual and then regress the summary measures on between-subject covariates