BLIMP PAPERS
    Workshops and Training
    Enders, C. K. (2023, April). An introduction to missing data analyses [Webinar]. American Psychological Association Training Session.
    Enders, C. K., & Woller, M. (2023, April). An introduction to Bayesian estimation and missing data imputation for educational research. Professional development workshop presented at the annual meeting of the American Educational Research Association. Chicago, IL.
    Enders, C. K. (2023, March). Longitindal modeling and missing data handling in Blimp. Workshop presented at the Advanced Techniques for Longitudinal Data Analysis in Social Science (ATLASS) conference. Bielefeld, Germany.
    Methodology Articles and Chapters
    Keller, B.T. (2024). A general approach to modeling latent variable interactions and nonlinear effects. Preprint available at osf.io/preprints/psyarxiv/w3bxh.
    Enders, C. K. (2023). Missing data: An update on the state of the art. Psychological Methods. Advanced online publication.
    Keller, B.T., & Enders, C. K. (2022). An investigation of factored regression missing data methods for multilevel models with cross-level interactions. Multivariate Behavioral Research. Advanced online publication.
    Enders, C. K. (2022). Fitting structural equation models with missing data. In R. Hoyle (Ed.), Handbook of structural equation modeling (2nd ed., pp. 223-241). New York: Guilford.
    Enders, C.K., & Hayes, T. (2022). Missing data handling for multilevel data. In A. O’Connell, B. McCoach, & B. Bell (Eds.), Multilevel modeling methods with introductory and advanced applications (pp. 535-566). Information Age: Greenwich, CT.
      Hayes, T., & Enders, C. K. (2022). Maximum likelihood and multiple imputation missing data handling: How they work, and how to make them work in practice. In H. Cooper (Ed.), APA Handbook of research methods in psychology (2nd ed., pp. 27-51). Washington, DC: American Psychological Association.
      Keller, B. T. (2022). An introduction to factored regression models with Blimp. Psych, 4, 10-37.
      Du, H., Enders, C.K., Keller, B.T., Bradbury, T., & Karney, B. (2021). A Bayesian latent variable selection model for nonignorable missingness. Multivariate Behavioral Research. Advanced Online Publication.
      Grund, S., Lüdtke, O., & Robitzsch, A. (2021). Multiple imputation of missing data in multilevel models with the R package mdmb: a flexible sequential modeling approach. Behavior Research Methods, 53, 2631–2649.
      Levy, R., & Enders, C.K. (2021). Full conditional distributions for Bayesian multilevel models with additive or interactive effects and missing data on covariates. Communications in Statistics, Advanced Online Publication.
      Vera, J. D., & Enders, C. K. (2021). Is item imputation always better? An investigation of missing questionnaires in longitudinal growth models. Structural Equation Modeling: A Multidisciplinary Journal, 28, 506–517.
      Enders, C. K., Du, H., & Keller, B. T. (2020). A model-based imputation procedure for multilevel regression models with random coefficients, interaction effects, and other nonlinear terms. Psychological Methods, 25, 88-112.
      Hayes, T. (2019). Flexible, Free Software for Multilevel Multiple Imputation: A Review of Blimp and jomo. Journal of Educational and Behavioral Statistics, 44, 625–641.
      Enders, C.K., Hayes, T., & Du, H. (2018). A comparison of multilevel imputation schemes for random coefficient models: Fully conditional specification and joint model imputation with random covariance matrices. Multivariate Behavioral Research, 53, 695-713.
      Enders, C. K., Keller, B. T., & Levy, R. (2018). A fully conditional specification approach to multilevel imputation of categorical and continuous variables. Psychological Methods, 23, 298-317.
      Applications
        Flynn, T.B., Gobel, P.M., Bishop, N.J., & Weimer, A.A. (2022). Early childhood hospitalization and problematic behaviors: A propensity score analysis. Journal of Child Health Care. Advanced Online Publication.
        Hess, K.L, Wolfs, A.C.F., Goldfarb, D., Evans, J.R., Hayes, T., Granitur, C., & McLaney, S. (2022). The influence of gender and other extralegal factors on student loan bankruptcy decisions. Public Policy, and Law. Advanced Online Publication.
        Joiner, R. J., Martinez, B. S., Nelson, N. A., & Bergeman, C. S. (2022). Within-person changes in religiosity, control beliefs, and subjective well-being across middle and late adulthood. Psychology and Aging. Advanced Online Publication.
        MacDonald, J.J, Jorge-Miller, A., Enders, C.K., McCannel, T.A., Beran, T.M., et al. (2021). Visual impairment and depression in uveal melanoma: Optimism and pessimism as moderators. Health Psychology, 40, 408-417.
        Metts, A. V., Yarrington, J. S., Zinbarg, R., Hammen, C., Mineka, S., Enders, C., & Craske, M. G. (2022). Early life adversity and risk for anxiety and depression: The role of interpersonal support. Development and Psychopathology, Advanced Online Publication.
        Parker, J.E., Enders, C.K., Mujahid, M.S., Epel, E.S., Laraia, B.A., Tomiyama, A.J. (2022). Prospective relationships between skin color satisfaction, body satisfaction, and binge eating in Black girls. Body Image, 41, 342-353.
        Technical Appendices
        Keller, B.T., & Enders, C.K. (2022). Online supplemental document: An investigation of factored regression missing data methods for multilevel models with cross-level interactions. Retrieved from www.appliedmissingdata.com/blimp-papers.
        Enders, C.K., Du, H., & Keller, B.T. (2020). Blimp technical appendix: Bayesian estimation for multilevel path models. Request a copy.
        Enders, C.K., Du, H., & Keller, B.T. (2019). Blimp technical appendix: Fully Bayesian model-based estimation and imputation for multilevel models. Retrieved from www.appliedmissingdata.com/blimp-papers.
        Enders, C.K., & Keller, B.T. (2019). Blimp technical appendix: Centering covariates in a Bayesian multilevel analysis. Request a copy.
        Enders, C.K., & Keller, B.T. (2019). Blimp technical appendix: Variance explained effect sizes for Bayesian multilevel analyses. Request a copy.