Authors@R: c(person(given="Briana", family="Cameron", email="briana.cameron@yale.edu", role=c("aut", "cph")), person(given="Denise", family="Esserman", email="denise.esserman@yale.edu", role="ctb"), person(given="Michael",family="Kane",email="michael.kane@yale.edu",role=c("cre", "ctb")))
outcome measure. The package contains functions to compute the required
sample size needed to detect a given preference, treatment, and selection
effect; alternatively, the package contains functions that can report the
study power given a fixed sample size. Finally, analysis functions are
provided to test each effect using either summary data (i.e. means,

Title: 2-Stage Preference Trial Design and Analysis

variances) or raw study data <doi:10.18637/jss.v094.c02>.

Title: 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) exploting an eliminate feature.
Computes pattern models for paired comparisons,
rankings, and ratings.  Some treatment of missing
Packaged: Thu Dec 11 10:58:02 2008; hatz

comparisons and derived paired comparison data (Likert type
items / ratings or rankings) using a loglinear approach.  Fits
loglinear Bradley-Terry model (LLBT) exploting an eliminate
feature. Computes pattern models for paired comparisons,
rankings, and ratings.  Some treatment of missing values (MCAR
Packaged: Thu Apr 16 12:17:21 2009; hatz

and MNAR). Fits latent class (mixture) models for paired
comparison, rating and ranking patterns.

Depends: stats, gnm (>= 1.0-0), colorspace
comparison, rating and ranking patterns using a nonparametric

feature.  Computes pattern models for paired comparisons,

Authors@R: c(person(given = "Reinhold", family = "Hatzinger", role = "aut"),
person(given = c("Marco", "Johannes"), family = "Maier",
email = "marco.maier@wu.ac.at", role = "cre"))
Depends: R (>= 3.0.0), stats, gnm (>= 1.0-0), colorspace
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 latent class (mixture) models for paired comparison, rating and ranking patterns using a non-parametric ML approach.