Nothing
PrepareTableWithBinaryData <-
function(table,
higher.is.better=NA,
rustlook=NA,
vpos=NA, pos=NA, neg=NA, vneg=NA,
level=95,
binary.measure="RR", summary.measure="SMD", method="DL",
seed=NA, sims=1){
# Input a table and impute all events for each study, then calculate Hedges' g and its variance.
#
# Args:
#
# Returns: A table with all events imputed, and with Hedges' g and its variance calculated.
## testing
# binary=TRUE; binary.measure="RR"; continuous.measure="SMD"; mean.sd=FALSE; higher.is.better=TRUE;
# vpos=NA; pos=NA; neg=NA; vneg=NA; rustlook=NA; level=95; method="DL"
## Avoid R CMD CHECK NOTE: "no visible binding for global variable".
expt.events <- expt.n <- ctrl.events <- ctrl.n <- NULL
## Assign effects (not based on CI of summary effect across published studies)
effect.sizes.list <- CompileEffectsToBeAssigned(table=table,
binary=TRUE,
higher.is.better=higher.is.better,
vpos=vpos, pos=pos, neg=neg, vneg=vneg,
binary.measure=binary.measure,
summary.measure=summary.measure, method=method,
level=level)
## If desired, assign all unpublished studies the same outlook
if(!is.na(rustlook)){
table <- AssignSameRustlook(table,rustlook)
# levels(table$outlook)
}
table <- ImputeBinaryEvents(table,effect.sizes.list,sims=sims)
table <- ConvertBinaryToEffectSize(table,measure=binary.measure)
return(table)
}
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