1 | getPartialRs(indicator, sampleData, sampleDesign, otherVariables = character())
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indicator |
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sampleData |
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sampleDesign |
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otherVariables |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (indicator, sampleData, sampleDesign, otherVariables = character())
{
modelVariables <- getVariables(indicator$model$formula, FALSE)
variables <- unique(c(modelVariables, otherVariables))
byVariables <- NULL
byCategories <- list()
for (variable in variables) {
pConditional <- getPartialRConditional(indicator, variable,
sampleData, sampleDesign)
pUnconditional <- getPartialRUnconditional(indicator,
variable, sampleData, sampleDesign)
byVariable <- data.frame(variable = variable, Pu = pUnconditional$Pu,
PuUnadj = pUnconditional$PuUnadj, PuSE = pUnconditional$PuSE,
Pc = pConditional$Pc, PcUnadj = pConditional$PcUnadj,
PcSEApprox = pUnconditional$PuSE)
byVariables <- rbind(byVariables, byVariable)
byCategory <- merge(pUnconditional$byCategory, pConditional$byCategory)
byCategories <- c(byCategories, list(byCategory))
}
names(byCategories) <- byVariables$variable
partialRs <- list(byVariables = byVariables, byCategories = byCategories)
return(partialRs)
}
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