micombine.F | R Documentation |
Several F
statistics from multiply imputed datasets are combined using
an approximation based on \chi^2
statistics
(see micombine.chisquare
).
micombine.F(Fvalues, df1, display=TRUE, version=1)
Fvalues |
Vector containing |
df1 |
Degrees of freedom of the numerator. Degrees of freedom of the
numerator are approximated by |
display |
A logical indicating whether results should be displayed at the console |
version |
Integer indicating which calculation formula should be used.
The default |
The same output as in micombine.chisquare
Allison, P. D. (2002). Missing data. Newbury Park, CA: Sage.
Enders, C. K. (2010). Applied missing data analysis. Guilford Press.
Grund, S., Luedtke, O., & Robitzsch, A. (2016). Pooling ANOVA results from multiply imputed datasets: A simulation study. Methodology, 12(3), 75-88. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1027/1614-2241/a000111")}
micombine.chisquare
#############################################################################
# EXAMPLE 1: F statistics for 5 imputed datasets
#############################################################################
Fvalues <- c( 6.76, 4.54, 4.23, 5.45, 4.78 )
micombine.F(Fvalues, df1=4 )
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 5 Imputed Data Sets
## F(4, 52.94)=3.946 p=0.00709
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