Planned Missing Data Designs for Research in Cognitive Development

Mijke Rhemtulla, Todd D. Little

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Data collection can be the most time- and cost-intensive part of developmental research. This article describes some long-proposed but little-used research designs that have the potential to maximize data quality (reliability and validity) while minimizing research cost. In planned missing data designs, missing data are used strategically to improve the validity of data collection in one of two ways. Multiform designs allow one to increase the number of measures assessed on each participant without increasing each participant's burden. Two-method measurement designs allow one to reap the benefits of a cost-intensive gold-standard measure, using a larger sample size made possible by a rougher, cheaper measure. We explain each method using examples relevant to cognitive development research. With the use of analysis methods that produce unbiased results, planned missing data designs are an efficient way to manage cost, improve data quality, and reduce participant fatigue and practice effects.

Original languageEnglish
Pages (from-to)425-438
Number of pages14
JournalJournal of Cognition and Development
Volume13
Issue number4
DOIs
StatePublished - Nov 2012

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