get_ests_bmlmi function

Von Hippel and Bartlett pooling of BMLMI method

Compute pooled point estimates, standard error and degrees of freedom according to the Von Hippel and Bartlett formula for Bootstrapped Maximum Likelihood Multiple Imputation (BMLMI).

get_ests_bmlmi(ests, D)

Arguments

• ests: numeric vector containing estimates from the analysis of the imputed datasets.
• D: numeric representing the number of imputations between each bootstrap sample in the BMLMI method.

Returns

a list containing point estimate, standard error and degrees of freedom.

Details

ests must be provided in the following order: the firsts D elements are related to analyses from random imputation of one bootstrap sample. The second set of D elements (i.e. from D+1 to 2*D) are related to the second bootstrap sample and so on.

References

Von Hippel, Paul T and Bartlett, Jonathan W8. Maximum likelihood multiple imputation: Faster imputations and consistent standard errors without posterior draws. 2021