Tukey's gh Distribution for Multiple Imputation

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Using Calibration to Improve Rounding in Imputation (2008, methodology): “This semiparametric approach is complementary to the use of flexible parametric models for imputing variables with skewed distributions (He and Raghunathan 2006).”
Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: a simulation assessment (2008, methodology): “As the popularity of inference by MI increases, new methods for creating MIs assuming more diverse class of distributions are emerging as well [14].”
Misspecifying the Shape of a Random Effects Distribution: Why Getting It Wrong May Not Matter (2011, methodology): “Neuhaus, Hauck and Kalbfleisch (1992), Neuhaus, Kalbfleisch and Hauck (1994) and Heagerty and Kurland (2001) developed analytic results to assess the impact of misspecification of the random effects distribution using the theory of inference under misspecified models (Huber, 1967; Akaike, 1973; Whit”