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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).

Usage

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.

Value

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