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Missing data

  • Joint Modelling Multiple Imputation is implemented in the R package jomo.

  • This allows for imputation of either continuous or discrete, participant-level  or study-level, and systematically or sporadically missing data.

  • A tutorial paper introducing the package has been published.

  • Several options are available to perform multiple imputation using the fully conditional specification approach.

  • In particular, the R package mice offers the implementation of one-stage multilevel multiple imputation methods for handling systematically and sporadically missing data in clustered data, and has built-in functions for the imputation of continuous and binary variables.

  • The functionalities of mice have been extended by the R package micemd, which offers the implementation of one-stage and two-stage multilevel imputation methods for continuous, binary and count variables.

  • Other R packages are available for dealing with missing values in clustered data (e.g. hmi or miceadds), but they are generally not dedicated to handle systematically and sporadically missing data jointly.    

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