print.miceFast_pool

Prints a concise summary of pooled multiple imputation results,
 showing the key inference columns: estimate, std.error, statistic, df, and p.value.

Fast imputations under the object-oriented programming paradigm.
Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'.
The biggest improvement in time performance can be achieved for a calculation where a grouping variable is used.
A single evaluation of a quantitative model for the multiple imputations is another major enhancement.
A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.

Maciej Nasinski

miceFast

Fast Imputations Using 'Rcpp' and 'Armadillo'

print.miceFast_pool function

<dl><dt>x</dt>
<dd>an object of class <code>"miceFast_pool"</code>, as returned by <code>pool</code>.</dd>
<dt>...</dt>
<dd>additional arguments (currently ignored).</dd></dl>

Arguments

Print method for pooled MI results — print.miceFast_pool

<dl>

<dt>x</dt>
<dd>an object of class <code>"miceFast_pool"</code>, as returned by <code>pool</code>.</dd>


<dt>...</dt>
<dd>additional arguments (currently ignored).</dd>

</dl>

print.miceFast_pool: Print method for pooled MI results

Description

Usage

Value

Arguments