A MATLAB library to generate scatter plots with bootstrapped confidence intervals and effect sizes based on means.
The library can be installed by following the github instructions: https://help.github.com/articles/cloning-a-repository/
Data should be in the csv file format and contain two columns with the headers: Identifiers and Values.
Identifiers are the labels of each data point, and Values are the data points (see the example below).
Note: All the sample data used in this tutorial are taken from S. Champely's anscombe2 dataset, and can be found in ContrastPlot_MATLAB/SampleData/.
Depending on the number of groups the data contain, the main function contrastplot produces various plots:
If the data have two different groups, contrastplot('TwoGroups_sample.csv') generates a two groups plot.
Running contrastplot('TwoGroups_sample.csv','Paired') generates a paired plot with the two groups data.
If the number of groups is an even number, a multiple groups plot will be automatically generated by contrastplot('MultipleGroups_sample.csv') command.
If there are more than two groups in the data, contrastplot('MultipleGroups_sample.csv') generates a shared control plot.
To combine two groups of data and compare to a third group, run contrastplot('MultipleGroups_sample.csv','mergeGroups').
For the data that contain more than three groups -and a number that is divisible by 3, contrastplot('MultipleGroups_sample.csv','mergeGroups') generates a multiple merged groups plot.
If the data contain more than three groups, contrastplot('MultipleGroups_sample.csv','mergeGroups') automatically generates a second plot in which all the groups are compared to the merged shared control.
