This function does inference for the χ^2 statistic based on multiply imputed datasets (see e.g. Enders, 2010, p. 239 ff.; Allison, 2002). This function is also denoted as the D_2 statistic.
1  micombine.chisquare(dk, df, display = TRUE, version=1)

dk 
Vector of chi square statistics 
df 
Degrees of freedom of χ^2 statistic 
display 
An optional logical indicating whether results should be printed at the R console. 
version 
Integer indicating which calculation formula should be used.
The default 
A vector with following entries
D 
Combined D_2 statistic which is approximately Fdistributed
with ( 
p 
The p value corresponding to 
df 
Denominator degrees of freedom 
df2 
Numerator degrees of freedom 
Alexander Robitzsch
Allison, P. D. (2002). Missing data. Newbury Park, CA: Sage.
Enders, C. K. (2010). Applied missing data analysis. Guilford Press.
See also mice::pool.compare
for a Wald test to compare two fitted models in the mice package.
1 2 3 4 5 6 7 8 9 10 11  #############################################################################
# EXAMPLE 1: Chi square values of analyses from 7 multiply imputed datasets
#############################################################################
# Vector of 7 chi square statistics
dk < c(24.957,18.051,18.812,17.362,21.234,18.615,19.84)
dk.comb < micombine.chisquare(dk=dk, df=4 )
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 7 Imputed Data Sets
## F(4,594.01)=4.486 p=0.00141
## Chi Square Approximation Chi2(4)=17.946 p=0.00126

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