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1crmda.KU.edu Todd D. Little University of Kansas Director, Quantitative Training Program Director, Center for Research Methods and Data Analysis Director,

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Presentation on theme: "1crmda.KU.edu Todd D. Little University of Kansas Director, Quantitative Training Program Director, Center for Research Methods and Data Analysis Director,"— Presentation transcript:

1 1crmda.KU.edu Todd D. Little University of Kansas Director, Quantitative Training Program Director, Center for Research Methods and Data Analysis Director, Undergraduate Social and Behavioral Sciences Methodology Minor Member, Developmental Psychology Training Program crmda. KU.edu Talk presented Society for Research in Child Development Advances in Missing Data and Implications for Developmental Science Advances in Missing Data and Implications for Developmental Science

2 2crmda.KU.edu Conclusions Imputing missing data is not cheating NOT imputing missing data is MOST likely to lead to errors in generalization! Plan for un-intentional missing data Plan intentionally missing data

3 3crmda.KU.edu Types of missing data

4 4crmda.KU.edu Modern Missing Data Analysis In 1978, Rubin proposed Multiple Imputation (MI) An approach especially well suited for use with large public-use databases. First suggested in 1978 and developed more fully in MI primarily uses the Expectation Maximization (EM) algorithm and/or the Markov Chain Monte Carlo (MCMC) algorithm. Beginning in the 1980’s, likelihood approaches developed. Multiple group SEM Full Information Maximum Likelihood (FIML). An approach well suited to more circumscribed models MI or FIML

5 5crmda.KU.edu Missing Data and Estimation: Missingness by Design Assess all persons, but not all variables at each time of measurement Control entry into study: estimate and control for retest effects, increase validity, decrease costs, increase power, etc. Randomly assign participants to their entry into a longitudinal study and/or to the occasions of assessment Key to providing unbiased estimates of growth or change

6 6crmda.KU.edu Form Common Variables Variable Set A Variable Set B Variable Set C 1Marker Variables ~1/3 of Variables None 2Marker Variables ~1/3 of Variables none~1/3 of Variables 3Marker Variables none~1/3 of Variables 3-Form Protocol

7 Expansions of 3-Form Design (Graham, Taylor, Olchowski, & Cumsille, 2006) crmda.KU.edu7

8 Expansions of 3-Form Design (Graham, Taylor, Olchowski, & Cumsille, 2006) crmda.KU.edu8

9 9 2-Method Planned Missing Design crmda.KU.edu

10 Controlled Enrollment GroupTime 1Time 2Time 3Time 4Time 5 1xxxxx 2xxxmissing 3xx x 4x xx 5 xxx 6xx x 7x x x 8 xx x 9x xx 10missingx xx 11missing xxx 10crmda.KU.edu

11 Optimal Growth Curve Design GroupTime 1Time 2Time 3Time 4Time 5 1xxxxx 6xxmissing x 7x x x 9x xx 11crmda.KU.edu

12 12crmda.KU.edu Combined Elements

13 13crmda.KU.edu The Sequential Designs

14 14crmda.KU.edu Transforming to Accelerated Longitudinal Assumes a MAR process, but if you plan for it and measure cohort-related influences, the impact will be easily estimated. In the analysis, cohort becomes a variable that is controlled for.

15 15crmda.KU.edu Thanks for your attention! Questions? crmda. KU.edu Talk presented Society for Research in Child Development Advances in Missing Data and Implications for Developmental Science Advances in Missing Data and Implications for Developmental Science

16 Update Dr. Todd Little is currently at Texas Tech University Director, Institute for Measurement, Methodology, Analysis and Policy (IMMAP) Director, “Stats Camp” Professor, Educational Psychology and Leadership IMMAP (immap.educ.ttu.edu) Stats Camp (Statscamp.org) 16www.Quant.KU.edu


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