Package: multifear 0.1.3

multifear: Multiverse Analyses for Conditioning Data

A suite of functions for performing analyses, based on a multiverse approach, for conditioning data. Specifically, given the appropriate data, the functions are able to perform t-tests, analyses of variance, and mixed models for the provided data and return summary statistics and plots. The function is also able to return for all those tests p-values, confidence intervals, and Bayes factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, & Krypotos (2022) <doi:10.1016/j.brat.2022.104072>.

Authors:Angelos-Miltiadis Krypotos [aut, cre, cph]

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Bug tracker:https://github.com/angelospsy/multifear/issues

On CRAN:

conditioningmultiverse

14 exports 2 stars 1.11 score 81 dependencies 7 scripts 291 downloads

Last updated 12 months agofrom:84adfe50dc. Checks:OK: 7. Indexed: yes.

Exports:bt_test_mfchop_cschop_csscombine_csexclusion_criteriaforestplot_mfinference_csinference_plotmixed_mfmultiverse_csrm_anova_mfrm_banova_mft_test_mfuniverse_cs

Dependencies:abindbackportsBayesFactorbayestestRbootbootstrapbroomcarcarDatacheckmateclicodacolorspacecontfraccowplotcpp11datawizardDerivdeSolvedoBydplyreffectsizeeffsizeellipticescezfansifarverforestplotgenericsggplot2gluegtablehypergeoinsightisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivparameterspbapplypbkrtestperformancepillarpkgconfigplyrpurrrquantregR6RColorBrewerRcppRcppEigenreshape2rlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr