pcX: Paired-Comparison Design Matrix
In eba: Elimination-by-Aspects Models

Description Usage Arguments Details Value References See Also Examples

Computes a paired-comparison design matrix.

1	pcX(nstimuli, omitRef = TRUE)

`nstimuli`	number of stimuli in the paired-comparison design
`omitRef`	logical, if `TRUE` (default), the first column corresponding to the reference category is omitted

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.

A matrix having (nstimuli - 1)*nstimuli/2 rows and nstimuli - 1 columns (if the reference category is omitted).

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

eba, thurstone, glm, balanced.pcdesign, linear2btl.

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)