pcX {eba} | R Documentation |
Paired-Comparison Design Matrix
Description
Computes a paired-comparison design matrix.
Usage
pcX(nstimuli, omitRef = TRUE)
Arguments
nstimuli |
number of stimuli in the paired-comparison design |
omitRef |
logical, if |
Details
The design matrix can be used when fitting a Bradley-Terry-Luce (BTL)
model or a Thurstone-Mosteller (TM) model by means of glm
or lm
. See Critchlow and Fligner (1991) for more details.
Value
A matrix having (nstimuli - 1)*nstimuli/2
rows and
nstimuli - 1
columns (if the reference category is omitted).
References
Critchlow, D.E., & Fligner, M.A. (1991). Paired comparison, triple comparison, and ranking experiments as generalized linear models, and their implementation in GLIM. Psychometrika, 56, 517–533. doi: 10.1007/bf02294488
See Also
eba
, thurstone
, glm
,
balanced.pcdesign
, linear2btl
.
Examples
data(drugrisk) # absolute choice frequencies
btl <- eba(drugrisk[, , 1]) # fit Bradley-Terry-Luce model using eba
summary(btl)
y1 <- t(drugrisk[, , 1])[lower.tri(drugrisk[, , 1])]
y0 <- drugrisk[, , 1][ lower.tri(drugrisk[, , 1])]
## Fit Bradley-Terry-Luce model using glm
btl.glm <- glm(cbind(y1, y0) ~ 0 + pcX(6), binomial)
summary(btl.glm)
## Fit Thurstone Case V model using glm
tm.glm <- glm(cbind(y1, y0) ~ 0 + pcX(6), binomial(probit))
summary(tm.glm)