Okay. I actually found the schematic representation of the model attached

to one of the posts. I wasn't able to view the covariance/correlation

matrix. At a quick glance, the model seems to be constructed properly.

Still, there could be a host of reasons a non p.d. matrix can happen, even

with a properly constructed model. I've now also read the thread since the

beginning, and from what I understand, it sounds like there are duplicates

of variables. That's a mistake that can be easily remedied. If that is NOT

the case (which sounds unlikely given David's diagnostics), then an

examination of the output is important.

Best,

Ryan

On Mon, Apr 22, 2013 at 2:06 PM, R B <

[hidden email]> wrote:

> There are many possibilities, which is why providing syntax is so

> important...I can't tell if the OP has provided the variance-covariance

> matrix (which is usually in embedded in an SPSS data file) being fed into

> AMOS or the actual AMOS syntax (simultaneous equations) to fit the model.

> Redundant variables in the variance-covariance matrix as well

> as problematic models could yield a not p.d result.

>

> If the OP provided the syntax, then, with little effort, someone (who had

> the time and access to AMOS) could fit the model to help the OP determine

> where the problem lies.

>

> Ryan

> On Mon, Apr 22, 2013 at 1:53 PM, Rich Ulrich <

[hidden email]> wrote:

>

>> To clarify David's comment --

>>

>> Your error message complains about a matrix is not "positive definite."

>>

>> If you actually did put the same variable twice into the list that results

>> in one covariance matrix, well, that is an error message that would show

>> it.

>>

>> I don't use Amos, but I presume that you have mis-applied the syntax for

>> presenting the model that you want. It seems less likely that Amos simply

>> can't do the model that you want.

>>

>> --

>> Rich Ulrich

>>

>>

>> > Date: Mon, 22 Apr 2013 09:07:29 -0700

>> > From:

[hidden email]>> > Subject: Re: AMOS ERROR MEASSAGE

>> > To:

[hidden email]>>

>> >

>> > Please elaborate what this means: "3 variables appearing twice in two

>> > different factors".

>> > You are SURELY NOT entering the same variables twice into the covariance

>> > matrix!

>> > That would be truly unfortunate and doomed to fail miserably.

>> > --

>> >

>> > kammel wrote

>> > > Hi

>> > >

>> > > I'm trying to assess the fit of an established model to my data. It

>> is a 6

>> > > factor model with 3 variables appearing twice in two different

>> factors. I

>> > > understand this may be a problem as I get this error message after

>> > > selecting 'calculate estimates':

>> > >

>> > > "An error occurred while attempting to fit the model.

>> > >

>> > > The sample moment matrix is no positive definite. It could be for the

>> > > following reasons:

>> > >

>> > > 1) The sample covariance matrix or the sample correlation matrix

>> ocntains

>> > > a data entry error.

>> > >

>> > > 2) The observed variables are linearly dependent (perhaps because the

>> > > sample size is too small).

>> > >

>> > > 3) The sample covariance matrix or sample correlation amtrix was

>> computed

>> > > from incomplete data using the method of 'pairwise deletion'

>> > >

>> > > 4) The sample coorelation matrix contains correlation coefficients

>> other

>> > > than product moment correlations (such as tetrachoric correlations)".

>> > >

>> > > I understand that the 3 variables appearing twice in two different

>> factors

>> > > are the causes of 'linear dependency', however as I am testing an

>> > > established model, I see no way around this.

>> > >

>> > > Can anyone suggets alternatives?

>> > >

>> > > Kindest

>> >

>> > ...

>>

>

>