MATLAB: To run NaN values with anova1

anovaMATLABmatrixnan

Hi, I have a matrix (8 x 621) and would like to run Anova1 between the 8 groups (rows). I have attached how the dataset looks like but when I run anova1, keyed in

p= anova1(dataset)

my p-value is 0. This does not seem right, may I know how I should correct it?

Thank you! 🙂

Best Answer

As per the anova1 help it expects groups to be arranged in columns, not rows:

"P = anova1(M) for a matrix M treats each column as a separate group,

and determines whether the population means of the columns are equal.

This form of anova1 is appropriate when each group has the same number

of elements (balanced ANOVA)."

So by simply transposing your matrix I get:

load('testdataset.mat')
P = anova1(testdatasetpfc_57_n1')

The problem was not actually related to the NaN values because anova1 automatically ignores them.

If you did want to remove the NaNs you could follow this procedure using the 'groups' input to anova1:

load('testdataset.mat')
groups = repmat(1:8,size(testdatasetpfc_57_n1,2),1)';
P = anova1(testdatasetpfc_57_n1(:),groups(:))

Hope this helps,

Related Solutions

MATLAB: Compare the Means between individual groups in anova

See if the multcompare (link) function will do what you want.

MATLAB: Avoiding for loop with anova1

I tooled around a bit with the anova1 function and reacquainted myself with the math. The below function appears to return the same values as looping through anova1, but a fair bit faster (I didn't time it), as I originally wanted. It could probably be improved substantially by vectorizing, etc., but it gets the job done. As Star Strider pointed out, it should never be used for significance testing unless coupled with a correction for multiple comparisons.

GDIM is the dimension along which groups are defined (columns in anova1) and MDIM is the dimension along which within groups measures are defined (rows in anova1). All F-statistics are calculated independently.

function [F,DFR,DFE]=NDfstat(X,GDIM,MDIM)
if exist('GDIM','var') && exist('MDIM','var')
   D=size(X);
   X=permute(X,[GDIM MDIM setdiff(1:numel(D),[GDIM MDIM])]);
end
D=size(X);
DFE = D(1)-1;
DFR = D(1)*(D(2)-1);
% X = X-repmat(mean(X,2),[1 D(2) ones(1,numel(D)-2)]);
   % anova1 does this, supposedly to improve accuracy, but it
   % seems to destroy calculation. Not sure what the deal is.
xm = squeeze(mean(X,2));
gm = squeeze(mean(xm));
SSE = squeeze(D(2)*sum((xm-repmat(shiftdim(gm,-1),[D(1) ones(1,numel(D)-1)])).^2));
SST = squeeze(sum(sum((X-repmat(shiftdim(gm,-2),[D(1:2) ones(1,numel(D)-1)])).^2)));
SSR = SST-SSE;
F = (SSE/DFE)./(SSR/DFR);
end

Best Answer

Related Solutions

MATLAB: Compare the Means between individual groups in anova

MATLAB: Avoiding for loop with anova1

Related Question