Factor Analysis: a covariance matrix is not positive definite

Hello,

I have a data set called Z2 that consists of 717 observations (rows) which are described by 33 variables (columns). The data is standardized by using ZSCORES. Additionally, there is no case for which would be recognized perfect linear dependancy (r=1). I've also cleared the data out of the variables with very low variance (var<0.1). The following figure plots the corresponding correlation matrix (in absolute values).

When I'm trying to run factor analysis using FACTORAN like following:

[Loadings1,specVar1,T,stats] = factoran(Z2,1);

I recive the following error:

" The data X must have a covariance matrix that is positive definite. "

Could you please tell me where is the problem? Is it due to low mutual dependancy among the used variables? In addition, what I can do about it?

Thank you.

Regards,

Vaclav

Answer 1

[Sonu Kumar]

No, This is happening because some of your variables are highly correlated.

As you can see, variable 9,10 and 15 have correlation almost 0.9 with their respective partners.

Try factoran after removing these variables. Regards