# random data for 4-category likert scale, 5 items
Q1 <- as.factor(sample(1:4, 500, replace = TRUE, prob = c(0.2, 0.3, 0.1, 0.4)))
Q2 <- as.factor(sample(1:4, 500, replace = TRUE, prob = c(0.5, 0.25, 0.15, 0.1)))
Q3 <- as.factor(sample(1:4, 500, replace = TRUE, prob = c(0.25, 0.1, 0.4, 0.25)))
Q4 <- as.factor(sample(1:4, 500, replace = TRUE, prob = c(0.1, 0.4, 0.4, 0.1)))
Q5 <- as.factor(sample(1:4, 500, replace = TRUE, prob = c(0.35, 0.25, 0.15, 0.25)))
likert_4 <- data.frame(Q1, Q2, Q3, Q4, Q5)
# create labels
levels_4 <- c("Independent", "Slightly dependent",
"Dependent", "Severely dependent")
# plot stacked frequencies of 5 (ordered) item-scales
sjp.stackfrq(likert_4, legend.labels = levels_4)
# -------------------------------
# Data from the EUROFAMCARE sample dataset
# -------------------------------
library(sjmisc)
data(efc)
# recveive first item of COPE-index scale
start <- which(colnames(efc) == "c82cop1")
# recveive first item of COPE-index scale
end <- which(colnames(efc) == "c90cop9")
# auto-detection of labels
sjp.stackfrq(efc[, c(start:end)])
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