The plot shows 'fit' by comparing the expected score based on the model (grey line) with the average scores based on the data (black line with dots) for groups of students with similar estimated ability.
# S3 method for class 'prms'
plot(
x,
item_id = NULL,
dataSrc = NULL,
predicate = NULL,
nbins = 5,
ci = 0.95,
add = FALSE,
col = "black",
col.model = "grey80",
...
)object produced by fit_enorm
which item to plot, if NULL, one plot for each item is made
data source, see details
an expression to subset data in dataSrc
number of ability groups
confidence interval for the error bars, between 0 and 1. Use 0 to suppress the error bars. Default = 0.95 for a 95% confidence interval
logical; if TRUE add to an already existing plot
color for the observed score average
color for the expected score based on the model
further arguments to plot
Silently, a data.frame with observed and expected values possibly useful to create a numerical fit measure.
The standard plot shows the fit against the sample on which the parameters were fitted. If dataSrc is provided, the fit is shown against the observed data in dataSrc. This may be useful for plotting the fit in different subgroups as a visual test for item level DIF. The confidence intervals denote the uncertainty about the predicted pvalues within the ability groups for the sample size in dataSrc (if not NULL) or the original data on which the model was fit.