getPRE: Proportional and Expected Proportional Reductions in Error

In davidaarmstrong/legR: Multidimensional Independent Dynamic IRT Models

Proportional and Expected Proportional Reductions in Error

Description

Calculates proportional reduction in error (PRE) and expected proportional reduction in error (epre) from Herron (1999).

Usage

getPRE(mod1, data)

Arguments

mod1	A model of class glm (with family binomial), polr or multinom for which (e)PRE will be calculated.
data	Data frame to be passed down to the function.

Details

Proportional reduction in error is calculated as a function of correct and incorrect predictions (and the probabilities of correct and incorrect predictions for ePRE).

Value

An object of class pre, which is a list with the following elements:

pre	The proportional reduction in error
epre	The expected proportional reduction in error
m1form	The formula for model 1
m2form	The formula for model 2
pcp	The percent correctly predicted by model 1
pmc	The percent correctly predicted by model 2
epcp	The expected percent correctly predicted by model 1
epmc	The expected percent correctly predicted by model 2

Author(s)

Dave Armstrong

References

Herron, M. 1999. Postestimation Uncertainty in Limited Dependent Variable Models. Political Analysis 8(1): 83–98.

davidaarmstrong/legR documentation built on Oct. 13, 2023, 1:08 p.m.