algo_effectiveness_poly: Computes the actual and predicted effectiveness of a given...

In airt: Evaluation of Algorithm Collections Using Item Response Theory

Computes the actual and predicted effectiveness of a given algorithm.

Description

This function computes the actual and predicted effectiveness of a given algorithm for different tolerance values.

Usage

algo_effectiveness_poly(mod, num = 1)

Arguments

mod	A fitted mirt model using the function irtmodel or R package mirt.
num	The algorithm number

Value

A list with the following components:

effective	The x,y coodinates for the actual and predicted effectiveness curves for algorithm num.
predictedEff	The area under the predicted effectiveness curve.
actualEff	The area under the actual effectiveness curve.

#'@examples set.seed(1) x1 <- sample(1:5, 100, replace = TRUE) x2 <- sample(1:5, 100, replace = TRUE) x3 <- sample(1:5, 100, replace = TRUE) X <- cbind.data.frame(x1, x2, x3) mod <- pirtmodel(X) out <- algo_effectiveness_poly(mod$model, num=1) out

airt documentation built on Aug. 8, 2023, 5:12 p.m.