Updated Mon, 06 Feb 2017 12:01:25 +0000
I never much liked the 'multcompare' function (much less the boxplot that Matlab uses for ANOVA), so I wrote this one to produce nicer graphs for factorial designs,
H= plotfdesign(T,G) plots means of vector T, their 95% conf. interval (as a box) and st. deviations (as a line), for each combination of factors defined in G. T is a numeric vector of data. G is a numeric or cell array of strings defining the groups (factors) for each data value. It returns a figure handle H which allows to set the characteristics of each component. Up to 4 factors are allowed. The first factor will be represented by adjacent bars in a plot, while the second factor (if present) is shown as different groups of bars in the same plot. Factors 3 and 4 (if present) will be columns and rows of subplots, respectively, in the figure.
The raw data is plotted (jittered) over each bar. The color of the dots (gray by default) is set to red if their distribution is not normal according to Lilliefors test (alpha=0.05).
Francisco de Castro (2023). plotfdesign(T,G,varargin) (https://www.mathworks.com/matlabcentral/fileexchange/60615-plotfdesign-t-g-varargin), MATLAB Central File Exchange. Retrieved .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > ANOVA > Repeated Measures and MANOVA >
Inspired by: notBoxPlot
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