Nothing
# score test
score <- function(responses) UseMethod("score", responses)
# score single subject's outcome
score.numeric <- function(responses) {
# score
s <- data.frame(
factor = names(test$factors),
score = double(5)
)
# factors
fs <- test$factors
# reversed item numbers
r <- test$reversed
# scale
scl <- test$scale$value
for (i in 1:length(fs)) {
f <- names(fs)[i]
ns <- fs[[f]]
# reversed item numbers
rns <- ns[ns %in% r]
# normal item numbers
nns <- ns[!(ns %in% r)]
m <- mean(
c(
responses[nns],
# reverse score
max(scl) + min(scl) - responses[rns]
),
na.rm = TRUE
)
s[s$factor == f, "score"] <- m
}
s
}
# score norm data
score.data.frame <- function(responses) {
# factors
fs <- test$factors
# reversed item numbers
r <- test$reversed
# scale
scl <- test$scale$value
for (i in 1:length(fs)) {
# factor name
f <- names(fs)[i]
# item numbers
ns <- fs[[i]]
# reversed item numbers
rns <- ns[ns %in% r]
# normal item numbers
nns <- ns[!ns %in% r]
# reverse and score
responses[, f] <- rowMeans(
cbind(
responses[, nns],
# reverse score
max(scl) + min(scl) - responses[, rns]
),
na.rm = TRUE
)
}
responses
}
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