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?"

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**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/makeTransparent.R

makeTransparent | R Documentation |

makeTransparent is an extension to ggplots which makes all the elements of the plot transparent except the data being displayed. This is useful to superimpose multiple plots, e.g. to generate plots with multiple error bars for example.

```
makeTransparent()
```

does not return anything; set the elements to transparent.

```
# make a basic plot
superbPlot(ToothGrowth, BSFactors = c("dose", "supp"),
variables = "len")
# make a basic plot with transparent elements
superbPlot(ToothGrowth, BSFactors = c("dose", "supp"),
variables = "len") + makeTransparent()
```

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?"

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