plot.ssra {SSRA}

Plot ssra

Description

Function for plotting the ssra object

Usage

## S3 method for class 'ssra'
plot(x, r.crt = NULL, r.sig = TRUE, d.sq = NULL,
  m.sig = TRUE, sig.col = TRUE,
  col = c("red2", "green4", "blue3", "black"),
  pch = c(1, 2, 0, 4), mar = c(3.5, 3.5, 1.5, 1), ...)

Arguments

x

requires the return object from the SSRA function

r.crt

minimal absolute correlation to be judged 'sequential'

r.sig

plot statistically significant correlations

d.sq

minimal effect size Cohen's d to be judged 'sequential'

m.sig

plot statistically significant mean difference

sig.col

significance in different colors

col

color code or name

pch

plotting character

mar

number of lines of margin to be specified on the four sides of the plot

...

further arguments passed to or from other methods

Details

Using this function, all item pairs are plotted on a graph by their correlation coefficients and their mean differences (Cohen's d). This graph is useful for defining (or changing) criteria regarding correlation coefficient and mean difference to judge whether an item pair is 'sequential' or 'equal'.

Author(s)

Takuya Yanagida [e-mail], Keiko Sakai [e-mail]

References

Takeya, M. (1991). A new test theory: Structural analyses for educational information. Tokyo: Waseda University Press.

See Also

SSRA, treegram, scatterplot

Examples

# Example data based on Takeya (1991)

# Sakai Sequential Relation Analysis
# ordering assesed according to the correlation coefficient and mean difference
exdat.ssra <- SSRA(exdat, output = FALSE)
plot(exdat.ssra)