In the context of your simulations and the use of one-way ANOVA in MATLAB, the concept of "groups" is crucial for setting up your analysis correctly.
Given that you are interested in assessing the variability introduced by the model, you should likely treat each simulation repeat as a separate group as each simulation repeat (n=140) represents a different set of conditions or a different treatment (variability embedded in the model). This way, you can evaluate whether the variability between repeats is significant compared to the variability within each repeat.
Assuming you have collected data from each simulation repeat, you can organize your data for ANOVA like this:
% Example data setup
% Assume MyData is a matrix where each column represents a simulation repeat
% and each row represents a data point within that repeat.
MyData = rand(100000, 140); % Replace with your actual data
% Reshape data into a single vector
data = MyData(:);
% Create a group vector indicating which simulation each data point belongs to
group = repelem(1:140, 100000)';
% Perform one-way ANOVA
[p, tbl, stats] = anova1(data, group);
