cmat: Confusion Matrix for a test.

In hthaa/cacPlot: Classification Accuracy and Consistency Plotting (cacPlot)

Description

Given a set of scores, their standard errors of measurement and the cutoff value of a test, calculate a confusion matrix indicating true and false positives and negatives under the assumption that sampling errors distribute normally around true-values.

Usage

cmat(score, se, cut)

Arguments

score	A vector of test-scores.
se	A vector of standard errors associated with the test-scores.
cut	A value indicating the cutoff-score of the test.

Value

A confusion matrix indicating the true- and false positive and negative rates of a test, given a specific cut-score and under the assumption that sampling errors distribute normally around true-values.

References

Rudner, L. (2005). Expected Classification Accuracy. Practical Assessment, Research and Evaluation. 10(13), p. 1-5.

hthaa/cacPlot documentation built on Dec. 18, 2019, 4:34 a.m.