FTres: Freeman-Tukey Residuals

In kequate: The Kernel Method of Test Equating

Freeman-Tukey Residuals

Description

Calculates the Freeman-Tukey residuals for log-linear models of frequency data. If the frequencies are assumed to be Poisson distributed, then the Freeman-Tukey residuals are approximately normal distributed.

Usage

FTres(obs, fit)

Arguments

obs	A numeric vector containing the observed frequencies.
fit	A numeric vector containing the estimated frequencies.

Details

For an observed frequency ni and the estimated frequency mi, the Freeman-Tukey residual FTi is defined as
FTi = √(ni)+√(ni+1)-√(4mi+1).

Value

A numeric vector containing the Freeman-Tukey residuals.

Author(s)

[e-mail]
[e-mail]
[e-mail]

References

Andersson, B., Branberg, K., and Wiberg, M. (2013). Performing the Kernel Method of Test Equating with the Package kequate. Journal of Statistical Software, 55(6), 1–25. <doi:10.18637/jss.v055.i06>

Holland, P.W, Thayer, D. (1998). Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions ETS Technical Report No 98-1.

See Also

glm

Examples

#Example data:
P<-c(5, 20, 35, 25, 15)
x<-0:4
glmx<-glm(P~I(x)+I(x^2), family="poisson", x=TRUE)
res<-FTres(glmx$y, glmx$fitted.values)

kequate documentation built on April 13, 2022, 9:06 a.m.