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prefmod (version 0.8-36)

prefmod-package: prefmod: Utilities to Fit Paired Comparison Models for Preferences

Description

Generates design matrix for analysing real paired comparisons and derived paired comparison data (Likert-type items/ratings or rankings) using a loglinear approach. Fits loglinear Bradley-Terry model (LLBT) exploiting an eliminate feature. Computes pattern models for paired comparisons, rankings, and ratings. Some treatment of missing values (MCAR and MNAR). Fits pattern mixture models using a non-parametric ML approach.

Arguments

Author

Reinhold Hatzinger, Marco J. Maier

Maintainer: Marco J. Maier (marco_maier@posteo.de)

Details

Package:prefmod
Type:Package
Version:packageDescription(pkg = "prefmod", fields = "Version")
Date:packageDescription(pkg = "prefmod", fields = "Date")
License:packageDescription(pkg = "prefmod", fields = "License")

References

Hatzinger, R., & Dittrich, R. (2012). prefmod: An R Package for Modeling Preferences Based on Paired Comparisons, Rankings, or Ratings. Journal of Statistical Software, 48(10), 1--31. https://www.jstatsoft.org/v48/i10/

Examples

Run this code
# mini example with three Likert items and two subject covariates

# using example data "xmpl" in the package
dsgnmat <- patt.design(xmpl, nitems = 3, resptype = "rating",
    ia = TRUE, cov.sel = "ALL")
head(dsgnmat)

# fit of Critchlov & Fligner (1991) Salad Dressings Data
pattR.fit(salad, nitems = 4)

# alternatively use glm() with patt.design()
sal <- patt.design(salad, nitems = 4, resptype = "ranking")
glm(y ~ A+B+C+D, data = sal, family = poisson)

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