psychotools (version 0.7-0)

summary.itemresp: Summarizing and Visualizing Item Response Data

Description

Summarizing and visualizing "itemresp" data objects.

Usage

# S3 method for itemresp
summary(object, items = NULL, abbreviate = FALSE,
    mscale = TRUE, simplify = TRUE, sep = " ", …)
  # S3 method for itemresp
plot(x, xlab = "", ylab = "", items = NULL,
    abbreviate = FALSE, mscale = TRUE, sep = "\n", off = 2, axes = TRUE,
    names = TRUE, srt = 45, adj = c(1.1, 1.1), …)

Arguments

object, x

an object of class "itemresp".

items

character or integer for subsetting the items to be summarized/visualized. By default, all items are used.

abbreviate

logical or integer. Should scale labels be abbreviated? Alternatively, an integer with the desired abbreviation length. The default is some heuristic based on the length of the labels.

mscale

logical. Should mscale values be used for printing/plotting? If FALSE, integers 0, 1, … are used.

simplify

logical. Should the summary table be collapsed into a matrix or returned as a list?

sep

character. A character for separating item labels from their corresponding scale labels (if any).

xlab, ylab, off, axes, …

arguments passed to spineplot.

names

logical or character. If TRUE, the names of the items are displayed on the x-axis. If FALSE, numbers of items are shown. Alternatively a character vector of the same length as the number of items can be supplied.

srt, adj

numeric. Angle (srt) and adjustment (adj) in case names (rather than numbers) are used as x-axis labels. These are passed to text.

Details

The plot method essentially just calls summary (passing on most further arguments) and then visualizes the result as a spineplot.

See Also

itemresp, spineplot

Examples

# NOT RUN {
## summary/visualization for verbal aggression data
data("VerbalAggression", package = "psychotools")
r <- itemresp(VerbalAggression$resp[, 1:6])
mscale(r) <- c("no", "perhaps", "yes")
summary(r)
plot(r)

## modify formatting of mscale
summary(r, abbreviate = 1)
summary(r, mscale = FALSE)

## illustration for varying mscale across items
## merge with additional random binary response
b <- itemresp(rep(c(-1, 1), length.out = length(r)),
  mscale = c(-1, 1), labels = "Dummy")
rb <- merge(r[, 1:2], b)
head(rb, 2)
## summary has NAs for non-existent response categories
summary(rb)
summary(rb, mscale = FALSE)
plot(rb, srt = 25)
plot(rb, mscale = FALSE)
# }