mi_dstat: Cohen's d Effect Size for Missingness Indicators
In miceadds: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description
Usage
Arguments
Value
Author(s)
Examples
Description
Computes Cohen's d effect size indicating whether missingness
on a variable is related to other variables (covariates).
Usage
1
mi_dstat(dat)
Arguments
dat
Data frame
Value
A matrix. Missingness indicators refer to rows and covariates
to columns.
Author(s)
Alexander Robitzsch
Examples
1
2
3
4
5
6
7
8
9
10
#############################################################################
# EXAMPLE 1: d effect size for missingness indicators data.ma01
#############################################################################
data(data.ma01)
dat <- data.ma01
# compute d effect sizes
md <- miceadds::mi_dstat(dat)
round( md , 3 )
miceadds documentation built on Aug. 25, 2017, 1:03 a.m.
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Description Usage Arguments Value Author(s) Examples
Description
Computes Cohen's d effect size indicating whether missingness on a variable is related to other variables (covariates).
Usage
1 | mi_dstat(dat)
|
Arguments
dat |
Data frame |
Value
A matrix. Missingness indicators refer to rows and covariates to columns.
Author(s)
Alexander Robitzsch
Examples
1 2 3 4 5 6 7 8 9 10 | #############################################################################
# EXAMPLE 1: d effect size for missingness indicators data.ma01
#############################################################################
data(data.ma01)
dat <- data.ma01
# compute d effect sizes
md <- miceadds::mi_dstat(dat)
round( md , 3 )
|
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We want your feedback!
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