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eba (version 1.10-0)

mbt: Mallows-Bradley-Terry Model

Description

Fits a Mallows-Bradley-Terry (MBT) model by maximum likelihood.

Usage

mbt(data, bootstrap = FALSE, nsim = 1000, ...)

Arguments

data

a data frame, the first t columns containing the ranks, the (t + 1)th column containing the frequencies

bootstrap

logical. Return a parametric bootstrap p-value?

nsim

number of bootstrap replicates

...

further aguments passed to simulate

Value

coefficients

a vector of parameter estimates (scale values) constrained to sum to unity

goodness.of.fit

the goodness of fit statistic including the likelihood ratio fitted vs. saturated model (-2logL), the degrees of freedom, the p-value of the corresponding chi-square distribution, and if bootstrap is TRUE the bootstrap p-value

perm.idx

the names of the non-zero frequency ranks

y

the vector of rank frequencies including zeros

mbt.glm

the output from a call to glm

Details

mbt provides a front end for glm. See Critchlow and Fligner (1991) and Mallows (1957) for details.

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. 10.1007/bf02294488

Mallows, C.L. (1957). Non-null ranking models. I. Biometrika, 44, 114--130. 10.1093/biomet/44.1-2.114

See Also

tartness, glm.

Examples

Run this code
# NOT RUN {
data(tartness)        # tartness rankings of salad dressings (Vargo, 1989)
mbt(tartness, bootstrap=TRUE, nsim=500)  # fit Mallows-Bradley-Terry model
# }

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