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## File Name: mi_dstat.R
## File Version: 0.06
################################################
# d effect size for missingness indicators
mi_dstat <- function(dat){
resp <- is.na(dat)
# means of missing data
miss_vars <- colnames(resp)[ colMeans( resp ) > 0 ]
MV <- length(miss_vars)
V <- ncol(dat)
dstat <- matrix( 0, nrow=MV, ncol=V )
rownames(dstat) <- miss_vars
colnames(dstat) <- colnames(dat)
for (vv in 1:MV){
# vv <- 5
dat_vv0 <- dat[ resp[, miss_vars[vv] ],, drop=FALSE ]
dat_vv1 <- dat[ ! resp[, miss_vars[vv] ],, drop=FALSE ]
m0 <- colMeans( dat_vv0, na.rm=TRUE )
m1 <- colMeans( dat_vv1, na.rm=TRUE )
sd0 <- apply( dat_vv0, 2, stats::sd, na.rm=TRUE)
sd1 <- apply( dat_vv1, 2, stats::sd, na.rm=TRUE)
d <- (m0-m1) / sqrt( ( sd0^2 + sd1^2 ) / 2 )
dstat[vv,] <- d
}
return(dstat)
}
#####################################################
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