[R] sem R: singular and Could not compute QR decomposition of Hessian

From: sanchez ana <paolas25mx_at_yahoo.com.mx>
Date: Fri, 04 Jun 2010 12:30:43 -0700 (PDT)

Can somebody help me with the following issue (SEM in R), please:

When I run the model (includes second order models) in R, it gives me the following:

1)       In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars,  :
  Could not compute QR decomposition of Hessian.
Optimization probably did not converge.

2)       I have aliased parameters and NaNS

or sometimes when I run it again I have the following message:

1)       Error in solve.default(C) :
  The system is computationally singular: condition number = 4.28182e-19 (it says so in Spanish)

Since the items are measured in likert scales I was using polychoric correlations, however, I saw that it can cause troubles, so I decided not to use it anymore. I also check the following:

1) Variables with variance 0 (I do not have)
2) Linear combinations of variables (I do not have high correlations)
3) I already used initial values for the aliased parameters
4) I do not have missing data
5) The eigenvalues of the S matrix are all positive (no zeros)
6) I calculate the determinant of the correlation matrix, adding one variable at a time, in order to look for multivariate dependencies, but the determinants are not cero, the lowest one is:0.0004054475


Since the model has constructs that are measured with only one item, I decided to connect directly the variable (item) to the other constructs.



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