plot.ssra | R Documentation |
Function for plotting the ssra object
## 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), ...)
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 |
Takea Semantic Structure Analysis (TSSA) and Sakai Sequential Relation Analysis (SSRA) are graphical approaches
Takuya Yanagida Keiko Sakai
Takeya, M. (1991). A new test theory: Structural analyses for educational information. Tokyo: Waseda University Press.
SSRA
, treegram
, scatterplot
## Not run:
# 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)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.