how to compute a linear mixed effect using nlmefit?
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Hi,
I'd like to fit a simple linear mixed model Y=XB+Zb+e with X the design matrix of the fixed effect (always the same size but not always the same values) and Z described subjects (which I specify as random)
here is the code I used
% generate data
for subject=1:10
x(:,subject) = [1:10]+randi(30,1);
coef(subject) = (3+rand(1));
y(:,subject) = coef(subject)*x(:,subject)+3*randn(10,1)- 5*mean(x(:,subject));
end
% create X, Y, subject for nlmefit
Y = y(:);
X = [x(:) ones(100,1)];
subject = sum(kron(diag(1:10),ones(10,1)),2);
% fit the data using 'model'
model = @(Betas,X) (X*Betas)
[Betas,PSI,stats] = nlmefit(X,Y,subject,[],model,[1 0])
The error is: Error using * Inner matrix dimensions must agree. Error in @(Betas,X)(X*Betas)
in a fixed effect Betas=pinv(X)Y and the fitted data = X*Betas, and that why i defined model this way, assuming that for each subject, parameters are fitted using 'model' ?? any idea what I am doing wrong ?
Thanks Cyril
2 个评论
Walter Roberson
2013-3-13
Do you in fact want algebraic matrix multiplication? Or do you want element-by-element multiplication which is the .* operator ?
采纳的回答
Tom Lane
2013-3-14
It looks like nlmefit invokes your model function with betas as a row vector. Try this:
model = @(Betas,X) (X*Betas(:))
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