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Recent publications

  1. Multiple imputation of longitudinal categorical data through bayesian…

    Vidotto, D., Vermunt, J., & Van Deun, K. (2019). Multiple imputation of longitudinal categorical data through bayesian mixture latent Markov models. Journal of Applied Statistics.
  2. Bayesian latent class models for the multiple imputation of categoric…

    Vidotto, D., Vermunt, J. K., & Van Deun, K. (2018). Bayesian latent class models for the multiple imputation of categorical data. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 14(2), 56-68.
  3. Bayesian latent class models for the multiple imputation of cross-sec…

    Vidotto, D. (2018). Bayesian latent class models for the multiple imputation of cross-sectional, multilevel and longitudinal categorical data. Proefschriftmaken.
  4. Bayesian multilevel latent class models for the multiple imputation o…

    Vidotto, D., Vermunt, J. K., & van Deun, K. (2018). Bayesian multilevel latent class models for the multiple imputation of nested categorical data. Journal of Educational and Behavioral Statistics, 43(5), 511-539.
  5. A mixed latent class Markov approach for estimating labour market mob…

    Bassi, F., Croon, M. A., & Vidotto, D. (2017). A mixed latent class Markov approach for estimating labour market mobility with multiple indicators and retrospective interrogation. Survey Methodology, 43(1), 107-124. http://www.statcan.gc.ca/pub/12-001-x/2017001/article/14820-eng.htm

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