Methodology Articles and Chapters
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.
      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.
      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.
      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
      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
      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.