Question

Which of the following ARE NOT potentially a cause of a non positive definite matrix?

Missing data.

Mis-specified model.

Analysis of a covariance matrix.

Small number of subjects relative to variables.

Answer 1

Which of the following ARE NOT potentially a cause of a non positive definite matrix?

Analysis of a covariance matrix.

The covariance matrix is not positive definite because it is singular. That means that at least one of your variables can be expressed as a linear combination of the others. You do not need all the variables as the value of at least one can be determined from a subset of the others. I would suggest adding variables sequentially and checking the covariance matrix at each step. If a new variable creates a singularity drop it and go on the the next one. Eventually you should have a subset of variables with a postive definite covariance matrix