mbt.Rd
Fits a Mallows-Bradley-Terry (MBT) model by maximum likelihood.
mbt(data, bootstrap = FALSE, nsim = 1000, ...)
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 |
mbt
provides a front end for glm
. See Critchlow and Fligner
(1991) and Mallows (1957) for details.
a vector of parameter estimates (scale values) constrained to sum to unity
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
the names of the non-zero frequency ranks
the vector of rank frequencies including zeros
the output from a call to glm
Florian Wickelmaier
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
Mallows, C.L. (1957). Non-null ranking models. I. Biometrika, 44, 114--130. doi: 10.1093/biomet/44.1-2.114
data(tartness) # tartness rankings of salad dressings (Vargo, 1989) mbt(tartness, bootstrap=TRUE, nsim=500) # fit Mallows-Bradley-Terry model#> Warning: glm.fit: fitted rates numerically 0 occurred#> #> Mallows-Bradely-Terry (MBT) models #> #> Parameter estimates: #> a b c d #> 0.0912 0.5182 0.2317 0.1588 #> #> Goodness of fit (-2 log likelihood ratio): #> G2(20) = 22.25, p = 0.3272, bootstrap p = 0.08 #>