Package: negligible 0.1.10

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]

negligible_0.1.10.tar.gz
negligible_0.1.10.zip(r-4.7)negligible_0.1.10.zip(r-4.6)negligible_0.1.10.zip(r-4.5)
negligible_0.1.10.tgz(r-4.6-any)negligible_0.1.10.tgz(r-4.5-any)
negligible_0.1.10.tar.gz(r-4.7-any)negligible_0.1.10.tar.gz(r-4.6-any)
negligible_0.1.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
negligible/json (API)

# Install 'negligible' in R:

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

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

Datasets:

perfectionism - Perfectionism Data

On CRAN:

equivalence-testing negligible-effect-statistical-testing negligible-effect-testing statistics

3.34 score 4 stars 11 scripts 532 downloads 16 exports 104 dependencies

Last updated from:6e83f24933. Checks:7 ERROR, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	ERROR	167
source / vignettes	OK	221
linux-release-x86_64	ERROR	167
macos-release-arm64	ERROR	106
macos-oldrel-arm64	ERROR	120
windows-devel	ERROR	127
windows-release	ERROR	104
windows-oldrel	ERROR	105
wasm-release	OK	140

Exports:neg.cat neg.cfi neg.cor neg.esm neg.indvars neg.intcat neg.intcont neg.normal neg.paired neg.pd neg.reg neg.rmsea neg.semfit neg.srmr neg.twocors neg.twoindmeans

Dependencies:abind arm askpass BH bit bit64 boot carData cellranger class cli clipr coda cpp11 crayon curl data.table DescTools digest dplyr e1071 Exact expm farver forcats foreign fs generics ggplot2 gld glue gtable haven hms httr isoband jsonlite kutils labeling lattice lavaan lifecycle lme4 lmom magrittr MASS Matrix MBESS mi mime minqa mnormt mvtnorm nlme nloptr nptest numDeriv OpenMx openssl openxlsx pbivnorm pillar pkgconfig plyr prettyunits progress proxy quadprog R6 rbibutils RColorBrewer Rcpp RcppEigen RcppParallel Rdpack readr readxl reformulas rematch reshape rlang rockchalk rootSolve rpf rstudioapi RUnit S7 scales sem semTools StanHeaders stringi sys tibble tidyselect tzdb utf8 vctrs viridisLite vroom withr WRS2 xtable zip

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Equivalence Testing for Categorical Variables	neg.cat print.neg.cat
Equivalence Tests for CFI	neg.cfi print.neg.cfi
Test for Lack of Association between Two Continuous Normally Distributed Variables: Equivalence-based correlation tests	neg.cor print.neg.cor
Test for Evaluating Substantial Mediation	neg.esm print.neg.esm
Negligible Effect Test for Variances of Independent Populations	neg.indvars print.neg.indvars
Test for Negligible Interaction between Two Categorical Variables with a Continuous Outcome	neg.intcat print.neg.intcat
Negligible Interaction Test for Continuous Predictors	neg.intcont print.neg.intcont
Negligible Effect Test for Normality of a Univariate Distribution	neg.normal print.neg.normal
Negligible Effect Test on the Difference between the Means of Dependent Populations	neg.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 Model	neg.reg print.neg.reg
Equivalence Tests for RMSEA	neg.rmsea print.neg.rmsea
Equivalence Tests for Fit Indices	neg.semfit
Equivalence Tests for SRMR	neg.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 Populations	neg.twoindmeans print.neg.twoindmeans
Perfectionism Data	perfectionism