DESCRIPTION

Package: rmBayes
Type: Package
Title: Performing Bayesian Inference for Repeated-Measures Designs
Version: 0.1.16
Date: 2024-02-19
Authors@R: 
    c(person(given = "Zhengxiao",
           family = "Wei",
           role = c("aut", "cre"),
           email = "zhengxiao@uvic.ca",
           comment = c(ORCID = "0000-0003-1866-2320")),
    person(given = "Farouk S.",
           family = "Nathoo",
           role = c("aut"),
           email = "nathoo@uvic.ca",
           comment = c(ORCID = "0000-0002-2569-3507")),
    person(given = "Michael E. J.",
           family = "Masson",
           role = c("aut"),
           email = "mmasson@uvic.ca",
           comment = c(ORCID = "0000-0002-5430-6078")))
Description: A Bayesian credible interval is interpreted with respect to posterior probability, 
    and this interpretation is far more intuitive than that of a frequentist confidence interval. 
    However, standard highest-density intervals can be wide due to between-subjects variability and tends 
    to hide within-subject effects, rendering its relationship with the Bayes factor less clear 
    in within-subject (repeated-measures) designs. 
    This urgent issue can be addressed by using within-subject intervals in within-subject designs, 
    which integrate four methods including the Wei-Nathoo-Masson (2023) <doi:10.3758/s13423-023-02295-1>, 
    the Loftus-Masson (1994) <doi:10.3758/BF03210951>, 
    the Nathoo-Kilshaw-Masson (2018) <doi:10.1016/j.jmp.2018.07.005>, 
    and the Heck (2019) <doi:10.31234/osf.io/whp8t> interval estimates.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
Biarch: true
Depends: 
    R (>= 3.5.0)
Imports: 
    methods,
    Rcpp (>= 0.12.0),
    RcppParallel,
    rstan (>= 2.26.0),
    rstantools (>= 2.1.1),
    stats
LinkingTo: 
    BH (>= 1.66.0),
    Rcpp (>= 0.12.0),
    RcppEigen (>= 0.3.3.3.0),
    RcppParallel,
    rstan (>= 2.26.0),
    StanHeaders (>= 2.26.0)
SystemRequirements: GNU make
URL: https://github.com/zhengxiaoUVic/rmBayes
BugReports: https://github.com/zhengxiaoUVic/rmBayes/issues
Suggests: 
    knitr,
    testthat,
    rmarkdown,
    covr
Config/testthat/edition: 3