Nothing
CompileEffectsToBeAssigned <-
function(table,
binary=TRUE, mean.sd=FALSE,
higher.is.better=TRUE,
vpos=NA, pos=NA, neg=NA, vneg=NA,
level=95,
binary.measure="RR", continuous.measure="SMD",
summary.measure="SMD", method="DL"){
# Assigns both (1) effect sizes based on the CI of the summary effect across published studies,
# and (2) effect sizes not based that CI.
#
# Args:
# table: the data set
# binary: True/False - The data is binary/count.
# higher.is.better: T/R - Higher counts/effect sizes are desired.
# mean.sd: T/F - The data is in the form of means and standard deviations.
# vpos: The effect size to assign studies with a "very positive" outlook.
# pos: The effect size to assign studies with a "positive" outlook.
# neg: The effect size to assign studies with a "negative" outlook.
# vneg: The effect size to assign studies with a "very negative" outlook.
# binary.measure:
# continuous.measure: The
# "SMD" = standardized mean difference (default)
# "SMDH" = standardized mean difference w/o assuming equal population variances
# in the two groups
#
# Returns: A list of effect sizes.
# Dependencies:
# Calls: ExtractPublishedStudies(), SetEffectSizesIndependentOfPub(), SetEffectSizesDependentOnPub()
## Extract published studies
pub <- ExtractPublishedStudies(table)
## Assign effects (not based on CI of summary effect across published studies)
eff.nopub <- SetEffectSizesIndependentOfPub(binary=binary,
higher.is.better=higher.is.better,
vpos=vpos, pos=pos, neg=neg, vneg=vneg)
## Assign effects based on CI of summary effect across published studies)
eff.onpub <- SetEffectSizesDependentOnPub(table,
binary=binary, mean.sd=mean.sd,
higher.is.better=higher.is.better,
level=level,
binary.measure=binary.measure, continuous.measure=continuous.measure,
summary.measure=summary.measure, method=method)
effect.sizes.list <- as.list(c(eff.nopub, eff.onpub))
names(effect.sizes.list) <- c("vpos", "pos", "noef", "neg", "vneg",
"vposcl", "poscl", "curr", "negcl", "vnegcl")
return(effect.sizes.list)
}
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