Summary Plots with Adjusted Error Bars

Vignettes

- Package overview
- README.md
- Adding labels to ``superb`` plots"
- (advanced) Alternate ways to decorrelate repeated measures from transformations"
- (advanced) Non-factorial within-subject designs in ``superb``"
- Customizing `superb` plots"
- Generating ready-to-analyze datasets with GRD"
- Plotting Cohen's d with ``superb``"
- Plotting frequencies using ``superb``"
- Plotting proportions with ``superb``"
- Plotting Reference Intervals with ``superb``"
- ``superb`` and SPSS"
- The making-of the figures in the article"
- Three steps to make your plot"
- Unequal variances, Welch test, Tryon adjustment, and ``superb``"
- Using a custom plot layout within ``superb``"
- Using a custom statistic with its error bar within ``superb``"
- Why use correlation-adjusted confidence intervals?"
- Why use difference-adjusted confidence intervals?"

194

55

41

**biasCorrectionTransform:**bias-correction transform**bootstrapPrecisionMeasures:**Bootstrapped measures of precision**CousineauLaurencelleLambda:**Cousineau-Laurencelle's lambda correction for...**dataFigure1:**Data for Figure 1**dataFigure2:**Data for Figure 2**dataFigure3:**Data for Figure 3**dataFigure4:**Data for Figure 4**geom_superberrorbar:**geom_superberrorbar for expanded error bar displays**GRD:**Generate random data**HyunhFeldtEpsilon:**Hyunh and Feldt's epsilon measure of sphericity**makeTransparent:**makes ggplots with transparent elements**MauchlySphericityTest:**Mauchly's test of Sphericity**measuresWithMissingData:**Measures with missing data**poolSDTransform:**pooled standard deviation transform**precisionMeasures:**Precision measures**precisionMeasureWithCustomDF:**Confidence intervals with custom degree of freedom**runDebug:**runDebug**showSignificance:**Annotate significance of results on plots**ShroutFleissICC1:**Shrout and Fleiss intra-class correlation functions**slope:**Effect description**subjectCenteringTransform:**subject-centering transform**summaryStatistics:**Additional summary statistics**superbData:**Obtain summary statistics with correct error bars.**superb-package:**superb: Summary Plots with Adjusted Error Bars**superbPlot:**summary plot of any statistics with adjusted error bars.**superbPlot.bar:**superbPlot 'bar' layout**superbPlot.boxplot:**superbPlot 'boxplot' layout**superbPlot.halfwidthline:**superbPlot 'halfwidthline' layout**superbPlot.line:**superbPlot 'line' layout**superbPlot.lineBand:**superbPlot 'lineBand' layout**superbPlot.point:**superbPlot 'point' layout**superbPlot.pointindividualline:**superbPlot point and individual-line layout for...**superbPlot.pointjitter:**superbPlot point-and-jitter dots layout**superbPlot.pointjitterviolin:**superbPlot point, jitter and violin plot layout**superbPlot.raincloud:**superbPlot 'raincloud' layout**superbShiny:**User Interface to get summary plot of any statistics with...**superbToWide:**superbToWide: Reshape long data frame to wide, suitable for...**TMB1964r:**Data of Tulving, Mandler, & Baumal, 1964 (reproduction of...**twoStepTransform:**two-step transform for subject centering and bias correction**WelchDegreeOfFreedom:**Welch's rectified degree of freedom**WinerCompoundSymmetryTest:**Winer's test of compound symmetry**Browse all...**

View source: R/functionsTransformation.R

subjectCenteringTransform | R Documentation |

`subjectCenteringTransform`

is a transformation that can
be applied to a matrix of data. the resulting matrix have means
that are centered on the grand mean, subject-wise \insertCitec05superb.

```
subjectCenteringTransform(dta, variables)
```

`dta` |
a data.frame containing the data in wide format; |

`variables` |
a vector of column names on which the transformation will be applied. the remaining columns will be left unchanged |

a data.frame of the same form as dta with the variables transformed.

This function is useful when passed to the argument `preprocessfct`

of `superbPlot()`

where it performs a modification of the data matrix.

Package overview
README.md
Adding labels to ``superb`` plots"
(advanced) Alternate ways to decorrelate repeated measures from transformations"
(advanced) Non-factorial within-subject designs in ``superb``"
Customizing `superb` plots"
Generating ready-to-analyze datasets with GRD"
Plotting Cohen's d with ``superb``"
Plotting frequencies using ``superb``"
Plotting proportions with ``superb``"
Plotting Reference Intervals with ``superb``"
``superb`` and SPSS"
The making-of the figures in the article"
Three steps to make your plot"
Unequal variances, Welch test, Tryon adjustment, and ``superb``"
Using a custom plot layout within ``superb``"
Using a custom statistic with its error bar within ``superb``"
Why use correlation-adjusted confidence intervals?"
Why use difference-adjusted confidence intervals?"

What can we improve?

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.

Close