Data engineering and BI courses are free!
Fits a Mallows-Bradley-Terry (MBT) model by maximum likelihood.
mbt(data, bootstrap = FALSE, nsim = 1000, ...)
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
a data frame, the first t columns containing the ranks, the (t + 1)th column containing the frequencies
logical. Return a parametric bootstrap p-value?
number of bootstrap replicates
further aguments passed to simulate
Florian Wickelmaier
mbt provides a front end for glm. See Critchlow and Fligner
(1991) and Mallows (1957) for details.
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. tools:::Rd_expr_doi("10.1007/bf02294488")
Mallows, C.L. (1957). Non-null ranking models. I. Biometrika, 44, 114--130. tools:::Rd_expr_doi("10.1093/biomet/44.1-2.114")
tartness, glm.
data(tartness) # tartness rankings of salad dressings (Vargo, 1989)
mbt(tartness, bootstrap=TRUE, nsim=500) # fit Mallows-Bradley-Terry model
Run the code above in your browser using DataLab