Adding return does not skip to the start of the next loop iteration, it just exits the function.
But you can easily return NaNs
function [height,weight] = body_metric(fileName,data_mat)
switch fileName
case 'Group 1'
data_mat = data_mat(2:20,:) % exclude made up outlier at row 1
case 'Group 2'
height = NaN;
weight = NaN;
return
case 'Group 3'
data_mat = data_mat([1:8,10:20],:) % exclude made up outlier at row 9
otherwise
... ?
end
height = data_mat(:,1); % 1st column are heights
weight = data_mat(:,2); % 2nd column are weights
end
And then simply check for those values within the loop:
for k = 1:10
fileName = filesMat(k);
data_mat = load(fileName); % data_mat is 20x2 matrix
[height,weight] = body_metric(fileName,data_mat);
if isscalar(height)&&isnan(height)&&isscalar(weight)&&isnan(weight)
continue
end
height_mean = mean(height);
weight_mean = mean(weight);
... the rest of your code.
end
Of course you do not need to use NaN, you should pick a class/size/value that will never be returned as valid data, and check for the existence of that class/size/value. E.g. empty arrays are easy to check for:
height = [];
weight = [];
...
if isempty(height)&&isempty(weight)
