nlsymiss dataset (581 children from the NLSY
with missing values on five variables), used in all examples.nlsymiss instead of being
wrapped in \dontrun{}.glemb() with
an odd number of imputations (m) caused results to
alternate between two distinct sets of imputations across successive
calls with the same seed. The imputation step now uses R’s own random
number generator instead of the Fortran RNG in the mix
package, whose internal state could not be fully reset between
calls.max.cells argument to glemb()
(default 500000). A pre-flight check now stops with an
informative error before glemb allocates any memory when
the nominal variables would produce more cells than this limit. Set
max.cells = Inf to disable the check.meanmodel argument to glemb().
"main" (default) constrains the continuous variable means
to depend only on the main effects of the categorical variables,
reducing the number of mean parameters from n_cells to
1 + sum(K_j - 1). "saturated" restores the
original cell-specific intercepts (unrestricted means).meanmodel value is stored in the returned object
and displayed by print() and summary().output = "mitml" option, returning a
mitml.list object compatible with
mitml::testEstimates().Initial release.
glemb(): multiple imputation for mixed continuous and
categorical data using the General Location Model with the EMB
algorithm.cat.interact = 3.cat.prior) for
sparse-cell stabilisation.empri).mids object compatible with mice::pool().print() and summary() methods for
glemb objects.