Package: superb 0.95.16
superb: Summary Plots with Adjusted Error Bars
Computes standard error and confidence interval of various descriptive statistics under various designs and sampling schemes. The main function, superbPlot(), return a plot. superbData() returns a dataframe with the statistic and its precision interval so that other plotting package can be used. See Cousineau and colleagues (2021) <doi:10.1177/25152459211035109> or Cousineau (2017) <doi:10.5709/acp-0214-z> for a review as well as Cousineau (2005) <doi:10.20982/tqmp.01.1.p042>, Morey (2008) <doi:10.20982/tqmp.04.2.p061>, Baguley (2012) <doi:10.3758/s13428-011-0123-7>, Cousineau & Laurencelle (2016) <doi:10.1037/met0000055>, Cousineau & O'Brien (2014) <doi:10.3758/s13428-013-0441-z>, Calderini & Harding <doi:10.20982/tqmp.15.1.p001> for specific references.
Authors:
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superb.pdf |superb.html✨
superb/json (API)
NEWS
# Install 'superb' in R: |
install.packages('superb', repos = c('https://dcousin3.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dcousin3/superb/issues
- TMB1964r - Data of Tulving, Mandler, & Baumal, 1964
- dataFigure1 - Data for Figure 1
- dataFigure2 - Data for Figure 2
- dataFigure3 - Data for Figure 3
- dataFigure4 - Data for Figure 4
error-barsplottingstatisticssummary-plotssummary-statisticsvisualization
Last updated 4 days agofrom:87270d7e9d. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 14 2024 |
R-4.5-win | OK | Sep 14 2024 |
R-4.5-linux | OK | Sep 14 2024 |
R-4.4-win | OK | Sep 14 2024 |
R-4.4-mac | OK | Sep 14 2024 |
R-4.3-win | OK | Sep 14 2024 |
R-4.3-mac | OK | Sep 14 2024 |
Exports:biasCorrectionTransformbootstrapPI.gmeanbootstrapPI.hmeanbootstrapPI.meanbootstrapPI.medianbootstrapPI.sdbootstrapPI.varbootstrapSE.gmeanbootstrapSE.hmeanbootstrapSE.meanbootstrapSE.medianbootstrapSE.sdbootstrapSE.varCI.fisherkurtosisCI.fisherskewCI.gmeanCI.hmeanCI.IQRCI.MADCI.meanCI.meanNArmCI.medianCI.pearsonskewCI.sdCI.varCIwithDF.meanCousineauLaurencelleLambdacustomextentfisherkurtosisfisherskewgeom_superberrorbargmeanGRDhmeanHyunhFeldtEpsilonMADmakeTransparentMauchlySphericityTestmeanNArmpearsonskewpoolSDTransformRexpressionrunDebugSE.fisherkurtosisSE.fisherskewSE.gmeanSE.hmeanSE.IQRSE.MADSE.meanSE.meanNArmSE.medianSE.pearsonskewSE.sdSE.varshowHorizontalSignificanceshowSignificanceshowVerticalSignificanceShroutFleissICC1ShroutFleissICC11ShroutFleissICC1kslopesubjectCenteringTransformsuperbDatasuperbPlotsuperbPlot.barsuperbPlot.boxplotsuperbPlot.corsetsuperbPlot.halfwidthlinesuperbPlot.linesuperbPlot.lineBandsuperbPlot.pointsuperbPlot.pointindividuallinesuperbPlot.pointjittersuperbPlot.pointjitterviolinsuperbPlot.raincloudsuperbShinysuperbToWidetwoStepTransformWelchDegreeOfFreedomWinerCompoundSymmetryTest
Dependencies:base64encbslibcachemclicolorspacecommonmarkcrayondigestfansifarverfastmapfontawesomeforeignfsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclelsrmagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigplyrpromisesR6rappdirsrbibutilsRColorBrewerRcppRdpackrlangsassscalesshinyshinyBSsourcetoolsstringistringrtibbleutf8vctrsviridisLitewithrxtable
(advanced) Alternate ways to decorrelate repeated measures from transformations
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superb and SPSS
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Using a custom statistic with its error bar within superb
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Why use difference-adjusted confidence intervals?
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on Sep 14 2024.Last update: 2022-11-17
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