micombine.chisquare.Rd
This function does inference for the \(\chi^2\) 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.
micombine.chisquare(dk, df, display=TRUE, version=1)
Vector of chi square statistics
Degrees of freedom of \(\chi^2\) statistic
An optional logical indicating whether results should be printed at the R console.
Integer indicating which calculation formula should be used.
The default version=1
refers to the correct formula as in Enders (2010),
while version=0
uses an incorrect formula as printed in Allison (2001).
The incorrect calculation version=0
was included in miceadds versions
smaller than version 2.0.
See also http://statisticalhorizons.com/wp-content/uploads/2012/01/combchi.sas.
A vector with following entries
Combined \(D_2\) statistic which is approximately \(F\)-distributed
with (df
, df2
) degrees of freedom
The p value corresponding to D
Numerator degrees of freedom
Denominator degrees of freedom
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.
#############################################################################
# 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 <- miceadds::micombine.chisquare(dk=dk, df=4 )
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 7 Imputed Data Sets
## F(4, 482.06)=4.438 p=0.00157