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Todd D. Little University of Kansas Director, Quantitative Training Program

Missing Data Analysis in Peer Relations Research. 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

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Todd D. Little University of Kansas Director, Quantitative Training Program

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  1. Missing Data Analysis in Peer Relations Research 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 Workshop presented 03-30-2011 @ Peer Relations Preconference crmda.KU.edu

  2. Briefly review the different types of missing data and how the missing data process can be recovered • Remember: imputing missing data is not cheating • NOT imputing missing data is more likely to lead to errors in generalization! • Introduce intentionally missing designs Road Map crmda.KU.edu

  3. Types of missing data crmda.KU.edu

  4. Effects of imputing missing data crmda.KU.edu

  5. Modern Missing Data Analysis MI or FIML • 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 1987. • 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 crmda.KU.edu

  6. Missing Data and Estimation:Missingness by Design • Assess all persons, but not all variables at each time of measurement • McArdle, Graham • Control entry into study: estimate and control for retesting 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 crmda.KU.edu

  7. 3-Form Intentionally Missing Design crmda.KU.edu

  8. 3-Form Protocol II crmda.KU.edu

  9. Expansions of 3-Form Design • (Graham, Taylor, Olchowski, & Cumsille, 2006) crmda.KU.edu

  10. Expansions of 3-Form Design • (Graham, Taylor, Olchowski, & Cumsille, 2006) crmda.KU.edu

  11. 2-Method Planned Missing Design crmda.KU.edu

  12. Controlled Enrollment crmda.KU.edu

  13. Growth Curve Design II crmda.KU.edu

  14. Growth Curve Design II crmda.KU.edu

  15. Combined Elements crmda.KU.edu

  16. The Sequential Designs crmda.KU.edu

  17. Transforming to Accelerated Longitudinal crmda.KU.edu

  18. Transforming to Episodic Time crmda.KU.edu

  19. Missing Data Analysis in Peer Relations Research Thanks for your attention! Questions? crmda.KU.edu Talk presented 03-30-2011 @ Peer Relations Preconference crmda.KU.edu

  20. 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 Email: yhat@ttu.edu IMMAP (immap.educ.ttu.edu) Stats Camp (Statscamp.org) www.Quant.KU.edu

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