c(person("Daniel","Heck",email="heck@uni-mannheim.de",role=c("aut","cre")),
person("Nina", "Arnold", email="arnold@uni-mannheim.de", role = c("aut","dtc")),
person("Denis", "Arnold", email="denis.arnold@uni-tuebingen.de", role = c("aut")),
person("Alexander", "Ly", email="a.ly@uva.nl", role = c("ctb")))
Daniel Heck [aut, cre],
Nina Arnold [aut, dtc],
Denis Arnold [aut],
Alexander Ly [ctb]
Rcpp (>= 0.12.6), runjags, stats, graphics, utils, grDevices,
coda, parallel, rjags, MASS, hypergeo

User-friendly analysis of hierarchical multinomial processing tree (MPT)
models that are often used in cognitive psychology. Implements the latent-trait
MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT
approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model
heterogeneity of participants. MPT models are conveniently specified by an
.eqn-file as used by other MPT software and data are provided by a .csv-file
or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored
Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides
tests of heterogeneity and MPT-tailored summaries and plotting functions.

c(person("Daniel W.", "Heck", email="heck@uni-mannheim.de", role=c("aut","cre")),
person("Nina R.", "Arnold", email="arnold@uni-mannheim.de", role = c("aut","dtc")),
person("Denis", "Arnold", email="denis.arnold@uni-tuebingen.de", role = c("aut")),
person("Alexander", "Ly", email="a.ly@uva.nl", role = c("ctb")))
Daniel W. Heck [aut, cre],
Nina R. Arnold [aut, dtc],
Denis Arnold [aut],
Alexander Ly [ctb]
Rcpp (>= 0.12.6), runjags, stats, graphics, utils, grDevices,
coda, parallel, rjags, MASS, hypergeo, logspline

User-friendly analysis of hierarchical multinomial processing tree (MPT)
models that are often used in cognitive psychology. Implements the latent-trait
MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT
approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model
heterogeneity of participants. MPT models are conveniently specified by an
.eqn-file as used by other MPT software and data are provided by a .csv-file
or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored
Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides
tests of heterogeneity and MPT-tailored summaries and plotting functions.
A detailed documentation is available in Heck, Arnold, & Arnold (2018)
<DOI:10.3758/s13428-017-0869-7>.