Package: negligible 0.1.8

negligible: A Collection of Functions for Negligible Effect/Equivalence Testing

Researchers often want to evaluate whether there is a negligible relationship among variables. The 'negligible' package provides functions that are useful for conducting negligible effect testing (also called equivalence testing). For example, there are functions for evaluating the equivalence of means or the presence of a negligible association (correlation or regression). Beribisky, N., Mara, C., & Cribbie, R. A. (2020) <doi:10.20982/tqmp.16.4.p424>. Beribisky, N., Davidson, H., Cribbie, R. A. (2019) <doi:10.7717/peerj.6853>. Shiskina, T., Farmus, L., & Cribbie, R. A. (2018) <doi:10.20982/tqmp.14.3.p167>. Mara, C. & Cribbie, R. A. (2017) <doi:10.1080/00220973.2017.1301356>. Counsell, A. & Cribbie, R. A. (2015) <doi:10.1111/bmsp.12045>. van Wieringen, K. & Cribbie, R. A. (2014) <doi:10.1111/bmsp.12015>. Goertzen, J. R. & Cribbie, R. A. (2010) <doi:10.1348/000711009x475853>. Cribbie, R. A., Gruman, J. & Arpin-Cribbie, C. (2004) <doi:10.1002/jclp.10217>.

Authors:Robert Cribbie [aut, cre], Udi Alter [aut], Nataly Beribisky [aut], Phil Chalmers [aut], Alyssa Counsell [aut], Linda Farmus [aut], Naomi Martinez Gutierrez [aut], Victoria Ng [ctb]

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negligible/json (API)

# Install 'negligible' in R:
install.packages('negligible', repos = c('https://cribbie.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cribbie/negligible/issues

Datasets:

On CRAN:

16 exports 5 stars 1.57 score 139 dependencies 10 scripts 979 downloads

Last updated 1 months agofrom:ab5689b73b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-winOKSep 07 2024
R-4.5-linuxOKSep 07 2024
R-4.4-winOKSep 07 2024
R-4.4-macOKSep 07 2024
R-4.3-winOKSep 07 2024
R-4.3-macOKSep 07 2024

Exports:neg.catneg.cfineg.corneg.esmneg.indvarsneg.intcatneg.intcontneg.normalneg.pairedneg.pdneg.regneg.rmseaneg.semfitneg.srmrneg.twocorsneg.twoindmeans

Dependencies:abindarmaskpassbackportsBHbitbit64bootbroomcarcarDatacellrangerclarabelclasscliclueclustercodacodetoolscolorspacecowplotcpp11crayoncurlCVXRdata.tableDEoptimDerivDescToolsdigestdoBydplyre1071ECOSolveRExactexpmezfansifarverforeachforeignfungibleGAgenericsggplot2gldgluegmpGPArotationgtablehmshttrisobanditeratorsjsonlitekutilslabelinglatticelavaanlifecyclelme4lmommagrittrMASSMatrixMatrixModelsMBESSmcmcMCMCpackmgcvmimicrobenchmarkmimeminqamnormtmodelrmunsellmvtnormnleqslvnlmenloptrnnetnptestnumDerivOpenMxopensslopenxlsxosqppbivnormpbkrtestpbmcapplypillarpkgconfigplyrprettyunitsprogressproxypurrrquadprogquantregR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcsdpreadxlrematchreshapereshape2rlangRmpfrrockchalkrootSolverpfRSpectrarstudioapiRUnitscalesscssemsemToolsSparseMStanHeadersstringistringrsurvivalsystibbletidyrtidyselectutf8vctrsviridisLitewithrWRS2xtablezip

Readme and manuals

Help Manual

Help pageTopics
Equivalence Testing for Categorical Variablesneg.cat print.neg.cat
Equivalence Tests for CFIneg.cfi print.neg.cfi
Test for Lack of Association between Two Continuous Normally Distributed Variables: Equivalence-based correlation testsneg.cor print.neg.cor
Test for Evaluating Substantial Mediationneg.esm print.neg.esm
Negligible Effect Test for Variances of Independent Populationsneg.indvars print.neg.indvars
Test for Negligible Interaction between Two Categorical Variables with a Continuous Outcomeneg.intcat print.neg.intcat
Negligible Interaction Test for Continuous Predictorsneg.intcont print.neg.intcont
Negligible Effect Test for Normality of a Univariate Distributionneg.normal print.neg.normal
Negligible Effect Test on the Difference between the Means of Dependent Populationsneg.paired print.neg.paired
Proportional Distance Function (post hoc function - not to be used independently)neg.pd
Test for Evaluating Negligible Effect Between a Predictor and Outcome in a Multiple Regression Modelneg.reg print.neg.reg
Equivalence Tests for RMSEAneg.rmsea print.neg.rmsea
Equivalence Tests for Fit Indicesneg.semfit
Equivalence Tests for SRMRneg.srmr print.neg.srmr
Test for Evaluating Negligible Effects of Two Independent or Dependent Correlation Coefficients: Based on Counsell & Cribbie (2015)neg.twocors print.neg.twocors
Negligible Effect Test on the Difference between the Means of Independent Populationsneg.twoindmeans print.neg.twoindmeans
Perfectionism Dataperfectionism