… , briefly reviewing the three phases in multiple imputation, the … various multiple imputation
multi-parameter test statistics, and review the limited existing literature on these test statistics. …

… context of multi-parameter or simultaneous inference, where we evaluate combinations of
… will see in Section 2.6 that it is not a suitable metric to evaluate multiple imputation methods. …

… The other two methods are those studied in this paper, namely multiple imputation by local
resampling or local semiparametric resampling, employing different sets of local weights w …

… multiple imputation. Although maximum likelihood estimation is perhaps the easiest method
to use in practice, psychological data … Evaluating a single estimate is done using the familiar …

… have missing data. We focus on multi-parameter tests, in line with the standard procedure
of … First, we provide a review of the challenges raised by missing responses on ordinal …

… Second, we provide a brief review of, and rationale for, multiple imputation in the SEM context.
Third, we describe the score test for multiply imputed data. To ensure that the exposition is …

… multiple imputation. Specifically type I error control and power after MI in a large simulation
study will be evaluated. … least equal power as the multi parameter tests that are currently used …

… I believe the time is ripe for multiple imputation to enter mainstream statistics. Computers and
… Before we review a number of simple fixes for the missing data in Section 1.3 let us take a …

… In section 4, we evaluate the performance of the multilevel imputation algorithms in
multilevel MICE. We illustrate the methods in an IPD meta-analysis in cardiovascular disease in …

… First, we give a brief review of multiple imputation, focusing primarily on Rubin’s (1987a)
pooling rules and single-parameter inference. Second, we give a detailed overview of the Wald …