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).
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
