Psychology 594L Quantitative Behavioral Methods Missing Data T/R 3:40 5:00 Lago W-0272

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1 Psychology 594L Quantitative Behavioral Methods Missing Data T/R 3:40 5:00 Lago W-0272 Instructor Todd Abraham Office W-053 Lagomarcino Hall Phone Office Hours (1/12-3/27) M 10-12; T 5-6 (3/30-5/08): M 9-12 Prerequisites Psych 501 or equivalent Course Goals As social science researchers, each of you will eventually encounter problems with missing data. While modern data collection methods can limit missingness, participants must always have the option of nonresponse to particular items. Problems with missing data are further compounded in longitudinal research where missingness within assessments and missingness across assessments are both likely to occur. Given the complexities involved with missing data, no single optimal solution that applies to all situations exists. Rather, my goal in this course is to establish concepts related to missing data mechanisms, develop a foundation in both traditional and modern methods to handle missing data, and introduce tools available to handle missing data in your own research. Recommended Text Muthén, L.K., & Muthén, B. O. ( ). Mplus User s Guide (7 th Ed.). Los Angeles, CA: Muthén & Muthén. Companion/Supplemental Readings Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data (2 nd ed.). Hoboken, NJ: John Wiley & Sons, Inc. Students with Disabilities Iowa State University is committed to assuring that all educational activities are free from discrimination and harassment based on disability status. All students requesting accommodations are required to meet with staff in Student Disability Resources (SDR) to establish eligibility. A Student Academic Accommodation Request (SAAR) form will be provided to eligible students. The provision of reasonable accommodations in this course will be arranged after timely delivery of the SAAR form to the instructor. Students are encouraged to deliver completed SAAR forms as early in the semester as possible. SDR, a unit in the Dean of Students Office, is located in room 1076, Student Services Building or online at Contact SDR by at disabilityresources@iastate.edu or by phone at for additional information. 1

2 Assessment Assignments Assignments will require independent analysis, interpretation, and reporting of statistical results using the methods we cover in class and various statistical analysis software packages (e.g., SPSS, SAS, Mplus, etc.), as well as published literature. I will provide any empirical data necessary for assignments that you will have one week to complete. Assignments: 80 points (4 20 points each) See Schedule for Dates Course Project For the course project, you will develop a strategy and conduct analyses to deal with missing data in your own research area. If you do not have data to use for the project, please see me as early as possible so that we can obtain/produce data that will suit your needs. Project Proposal: 10 points Friday 02/27/15 The project requires a short proposal (1-2 pp.) describing the data you intend to use, the missing data problem(s) in those data, and the analysis/analyses you plan to conduct. Your proposal can include supporting figures. Course Project: 110 points Monday 03/30/15 Your completed project should include a short introduction to the research question/hypotheses, description of the methods/measures, a detailed description of your approach to handling the missing data, a summary of the analysis plan/results, and a short discussion of what your analyses reveal. Final Course Grades Course grades will be determined based on the total number of points earned on the assignments, project proposal, and course project based on the scale below. Delivery and Format Points Grade Points Grade Points Grade A B C A B C B C+ < 138 D Assignments, project proposals, and final projects can be submitted via electronic or paper copy (your choice). I assume most of you come from social science areas where APA format is dominant but strict adherence to APA style is not required. My only request regarding format involves use of tables or figures as supporting materials. Where tables/figures are included, please insert them at their point of relevance (inline), rather than adding tables/figures to the end of your document. 2

3 Tentative Course Schedule Week Topics Required Readings and Assignments Schafer, J. L., & Graham, J. W. (2002). Missing data: Out view of the state of the art. Psychological Methods, 7, doi: // X /17 02/19 Course Introduction Types of Missing Data Missing Data Mechanisms Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, doi: /annurev.psych Jeličić, H., Phelps, E., & Lerner, R. M. (2009). Use of missing data methods in longitudinal studies: The persistence of bad practices in developmental psychology. Developmental Psychology, 45, doi: /a Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57, doi: /a Assignment #1 - Literature Evaluation Due Tuesday 2/24/15 Project Proposal Due by Friday 02/27/ /24 02/26 Traditional Methods Single-Imputation Methods Engels, J. M., & Diehr, P. (2003). Imputation of missing longitudinal data: A comparison of methods. Journal of Clinical Epidemiology, 56, doi: /S (03) Hedeker, D., Mermelstein, R. J., & Demirtas, H. (2007). Analysis of binary outcomes with missing data: Missing = smoking, last observation carried forward, and a little multiple imputation. Addiction, 102, doi: /j x Tuesday: Assignment #1 (Literature Evaluation) Due Thursday: Receive Assignment #2 Single Imputation Methods Due Thursday 3/05/15 Friday: Project Proposal Due 3

4 Week Topics Required Readings and Assignments Enders, C. K. (2001). A primer on maximum likelihood algorithms available for use with missing data. Structural Equation Modeling: A Multidisciplinary Journal, 8, doi: /S SEM0801_7 3 03/03 03/05 Model-Based Approaches ML Methods Acock, A. C. (2012). What to do about missing values. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology, Vol. 3: Data Analysis and research publication (pp ). Washington, DC: APA. doi: / Graham, J. W. (2003). Adding missing-data-relevant variables to FIML-based structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 10, doi: /S SEM1001_4 Thursday: Receive Assignment #3: FIML Methods Due Thursday 3/12/15 Assignment #2 (Single Imputation Methods) Due 4 03/10 03/12 ML Methods (cont.) NMAR Problems Possible Solutions Enders, C. K., Baraldi, A. N., & Cham, H. (2014). Estimating interaction effects with incomplete predictor variables. Psychological Methods, 19, doi: /a Hedeker, D., & Gibbons, R. D. (1997). Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychological Methods, 2, doi: / X Enders, C. K. (2011). Missing not at random models for latent growth curve analyses. Psychological Methods, 16, doi: /a Thursday: Receive Assignment #4: MI and NMAR Applications Due Thursday 3/26/15 Assignment #3 (FIML Methods) Due 4

5 Week Topics Required Readings and Assignments 5 03/17 03/19 No Class Meetings SPRING BREAK 6 03/24 03/26 Planned Missingness Interesting Problems Graham, J. W., Taylor, B. J., Olchowski, A. E., & Cumsille, P. E. (2006). Planned missing data designs in psychological research. Psychological Methods, 11, DOI: / X Rhemtulla, M., Jia, F., Wu, W., & Little, T. D. (2014). Planned missing data designs to optimize the efficiency of latent growth parameter estimates. International Journal of Behavior Development, 38, doi: / [Blackboard] Thursday: Assignment #4 (MI & NMAR) Due FINAL PROJECT PAPER DUE MONDAY 03/30/15 5