sjt.stackfrq: Summary of stacked frequencies as HTML table

Description

Shows the results of stacked frequencies (such as likert scales) as HTML table. This function is useful when several items with identical scale/categories should be printed as table to compare their distributions (e.g. when plotting scales like SF, Barthel-Index, Quality-of-Life-scales etc.).

Usage

sjt.stackfrq(items, weightBy = NULL, title = NULL, varlabels = NULL,
  breakLabelsAt = 40, valuelabels = NULL, breakValueLabelsAt = 20,
  sort.frq = NULL, alternateRowColors = FALSE, digits = 2,
  showN = FALSE, showTotalN = FALSE, showNA = FALSE, labelNA = "NA",
  showSkew = FALSE, showKurtosis = FALSE, digits.stats = 2,
  skewString = "Skew", kurtosisString = "Kurtosis", file = NULL,
  encoding = NULL, CSS = NULL, useViewer = TRUE, no.output = FALSE,
  remove.spaces = TRUE)

Arguments

Value

Invisibly returns

the web page style sheet (page.style),
the web page content (page.content),
the complete html-output (output.complete) and
the html-table with inline-css for use with knitr (knitr)

for further use.

Details

See 'Details' in sjt.frq.

Examples

Run this code

# -------------------------------
# random sample
# -------------------------------
# prepare data for 4-category likert scale, 5 items
likert_4 <- data.frame(as.factor(sample(1:4,
                                        500,
                                        replace = TRUE,
                                        prob = c(0.2, 0.3, 0.1, 0.4))),
                       as.factor(sample(1:4,
                                        500,
                                        replace = TRUE,
                                        prob = c(0.5, 0.25, 0.15, 0.1))),
                       as.factor(sample(1:4,
                                        500,
                                        replace = TRUE,
                                        prob = c(0.25, 0.1, 0.4, 0.25))),
                       as.factor(sample(1:4,
                                        500,
                                        replace = TRUE,
                                        prob = c(0.1, 0.4, 0.4, 0.1))),
                       as.factor(sample(1:4,
                                        500,
                                        replace = TRUE,
                                        prob = c(0.35, 0.25, 0.15, 0.25))))
# create labels
levels_4 <- c("Independent",
              "Slightly dependent",
              "Dependent",
              "Severely dependent")

# create item labels
items <- c("Q1", "Q2", "Q3", "Q4", "Q5")

# plot stacked frequencies of 5 (ordered) item-scales
sjt.stackfrq(likert_4, valuelabels = levels_4, varlabels = items)


# -------------------------------
# Data from the EUROFAMCARE sample dataset
# Auto-detection of labels
# -------------------------------
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")

sjt.stackfrq(efc[, c(start:end)],
             alternateRowColors = TRUE)

sjt.stackfrq(efc[, c(start:end)],
             alternateRowColors = TRUE,
             showN = TRUE,
             showNA = TRUE)


# --------------------------------
# User defined style sheet
# --------------------------------
sjt.stackfrq(efc[, c(start:end)],
             alternateRowColors = TRUE,
             showTotalN = TRUE,
             showSkew = TRUE,
             showKurtosis = TRUE,
             CSS = list(css.ncol = "border-left:1px dotted black;",
                        css.summary = "font-style:italic;"))