Analysis of Sensory and Consumer Data in a Mixed Model Framework
c(person("Alexandra", "Kuznetsova", role = c("aut", "cre"),
email = "alku@dtu.dk"),
person("Per", "Bruun Brockhoff", role = c("aut", "ths")),
person("Rune", "Haubo Bojesen Christensen", role = "aut"))
Hmisc, plyr, doBy, xtable, reshape2, ggplot2, shiny, shinyBS,
lme4 (>= 1.1)
Functions that facilitate analysis of
Sensory as well as Consumer data within a mixed effects model
framework. The so-called mixed assessor models,
that correct for the scaling effect are implemented.
The generation of the d-tilde plots forms part of the package.
The shiny application provides GUI for the functionalities.
Alexandra Kuznetsova [aut, cre],
Per Bruun Brockhoff [aut, ths],
Rune Haubo Bojesen Christensen [aut]

Hmisc, parallel, plyr, doBy, xtable, reshape2, ggplot2, shiny,
shinyBS, lme4
Functions that facilitate analysis of
Sensory as well as Consumer data within a mixed effects model
framework are provided. The so-called mixed assessor models,
that correct for the scaling effect are implemented.
The generation of the d-tilde plots forms part of the package.
The shiny application for the  functionalities
forms part of the package.

c(person("Alexandra", "Kuznetsova", role = c("aut"),
email = "alku@dtu.dk"),
person("Per", "Bruun Brockhoff", role = c("aut", "ths", "cre"),
email = "perbb@dtu.dk"),
person("Rune", "Haubo Bojesen Christensen",
role = c("aut"),
email = "Rune@ChristensenStatistics.dk"))
Hmisc, plyr, doBy, xtable, reshape2, ggplot2, shiny, shinyBS,
lme4 (>= 1.1), MASS
Functions that facilitate analysis of
Sensory as well as Consumer data within a mixed effects model
framework. The so-called mixed assessor models,
that correct for the scaling effect are implemented.
The generation of the d-tilde plots forms part of the package.
The shiny application provides a GUI for the functionalities.
Alexandra Kuznetsova [aut],
Per Bruun Brockhoff [aut, ths, cre],
Rune Haubo Bojesen Christensen [aut]

Sensitivity Analysis for Case-Control Studies
This package performs sensitivity analysis for
case-control studies in which some cases may meet a more narrow
definition of being a case compared to other cases which only
meet a broad definition.  The sensitivity analyses are
described in Small, Cheng, Halloran and Rosenbaum (2012, "Case
Definition and Sensitivity Analysis", working paper).  The
functions sens.analysis.mh and sens.analysis.aberrant.rank
provide sensitivity analyses based on the Mantel-Haenszel test
statistic and aberrant rank test statistic as described in
Rosenbaum (1991, "Sensitivity Analysis for Matched Case Control
Studies", Biometrics); see also Section 1 of Small et al.  The
function adaptive.case.test provides adaptive inferences as
described in Section 5 of Small et al.  The function
adaptive.noether.brown provides a sensitivity analysis for a
matched cohort study based on an adaptive test.  The other
functions in the package are internal functions.