Planned Missing Data Designs for Developmental Researchers

Planned missing data designs allow researchers to collect incomplete data from participants by randomly assigning participants to have missing items on a survey (multiform designs) or missing measurement occasions in a longitudinal design (wave missing designs) or by administering an intensive measu...

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Bibliographic Details
Published inChild development perspectives Vol. 7; no. 4; pp. 199 - 204
Main Authors Little, Todd D., Rhemtulla, Mijke
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.12.2013
Blackwell
Wiley Subscription Services, Inc
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Summary:Planned missing data designs allow researchers to collect incomplete data from participants by randomly assigning participants to have missing items on a survey (multiform designs) or missing measurement occasions in a longitudinal design (wave missing designs) or by administering an intensive measure to a small subsample of a larger dataset (two‐method measurement designs). When these designs are implemented correctly and when missingness is dealt with using a modern approach, the cost of data collection is lowered (sometimes dramatically) and reduced participant burden may result in higher validity as well as lower rates of unplanned missing data. In reviewing these planned missing designs, we briefly describe results of ongoing research on bias and power associated with each.
Bibliography:University of Kansas
Social Sciences and Humanities Research Council of Canada
ArticleID:CDEP12043
istex:4EDA3D98A2F4A8510C5833F16BB54D2492485E83
ark:/67375/WNG-29082869-Q
NSF - No. 1053160
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1750-8592
1750-8606
DOI:10.1111/cdep.12043