Implements the JSON, INI, YAML and TOML parser for R setting and writing of configuration file. The functionality of this package is similar to that of package 'config'.

R functions for criterion profile analysis, Davison and Davenport (2002) <doi:10.1037/1082-989X.7.4.468> and meta-analytic criterion profile analysis, Wiernik, Wilmot, Davison, and Ones (2020) <doi:10.1037/met0000305>. Sensitivity analyses to aid in interpreting criterion profile analysis results are also included.

Produces descriptive interpretations of confidence intervals.
    Includes (extensible) support for various test types, specified as sets
    of interpretations dependent on where the lower and upper confidence limits
    sit. Provides plotting functions for graphical display of interpretations.

Calculates classic and/or bootstrap confidence intervals for
    many parameters such as the population mean, variance, interquartile
    range (IQR), median absolute deviation (MAD), skewness, kurtosis,
    Cramer's V, odds ratio, R-squared, quantiles (incl. median),
    proportions, different types of correlation measures, difference in
    means, quantiles and medians. Many of the classic confidence intervals
    are described in Smithson, M. (2003, ISBN: 978-0761924999). Bootstrap
    confidence intervals are calculated with the R package 'boot'. Both
    one- and two-sided intervals are supported.

The main function calculates confidence intervals (CI) for Mixed Models, utilizing both classical estimators from the lmer() function in the 'lme4' package and robust estimators from the rlmer() function in the 'robustlmm' package, as well as the varComprob() function in the 'robustvarComp' package. Three methods are available: the classical Wald method, the wild bootstrap, and the parametric bootstrap. Bootstrap methods offer flexibility in obtaining lower and upper bounds through percentile or BCa methods. More details are given in Mason, F., Cantoni, E., & Ghisletta, P. (2021) <doi:10.5964/meth.6607> and Mason, F., Cantoni, E., & Ghisletta, P. (2024) <doi:10.1037/met0000643>.