Posted by
David Matheson-3 on
Jun 27, 2012; 3:57pm
URL: http://spssx-discussion.165.s1.nabble.com/SEM-in-AMOS-questions-on-error-terms-covariance-and-negative-chi-square-value-tp5713770p5713844.html
Hi Nick,
You don't mention whether you encountered the negative chi-square on the
first run of the model file. However, I think that you've encountered a
bug in AMOS 20 that is triggered on subsequent runs of a model file where
there is missing data and the computer's local settings use a comma as a
decimal point. There is a fix available at:
http://www-01.ibm.com/support/docview.wss?uid=swg24032174You will need to register on the site to download the fix pack. In
the "Download description" area, you'll see a "Fix list" link that
provides descriptions of the issues corrected by the fix pack. This issue
is described in more detail in the third link in the fix list. (You'll
also need to be registered on the site to open the description.)
The negative chi-square and other strange values in subsequent
runs of the model are due to the *.AmosP file, which is created
the first time you fit a model to a specific subset of variables
in a specific data file that has missing values. The *.AmosP
file contains the discrepancies for the independence and
saturated models. In the first analysis, the discrepancies are
calculated. On subsequent analyses of the same subset of
variables in the same data file, the discrepancies for the
independence and saturated models are read from the *.AmosP
file.
A temporary workaround is to delete any AmosP files in the
working directory, i.e. the directory with the AMOS program
(.amw) file, before running each analysis.
David Matheson
IBM SPSS Support
On Mon, 25 Jun 2012 02:58:59 -0700, Nick <
[hidden email]> wrote:
>Dear all,
>
>I am pretty new to SEM in AMOS and would be very grateful for your help
with
>a few questions regarding my model (attached with standardized estimates),
>specified as follows:
>- four predictors (P1 to P4) of one dependent variable (AV1)
>- AV 1 in turn predicts a second dependent variable (AV2), AV2 being a
>latent variable with three indicator variables (outcome1 to outcome 3)
>- four variables, that I want to control for, (CV1 to CV4) also influence
>AV2.
>
>I have a sample of n=170 with some missing data. Data are mean scores from
>questionnaires and are not skewed.
>
>Here are my questions:
>- is it necessary to use the double-headed covariance arrows between all
>predictor variables (P1 to P4; and CV1 to CV4)
>
>- are the error terms correctly placed and specified with regression
weight
>= 1 ?
>
>- why do I get a chi square value that is likely to be nonsensical:
>Number of distinct sample moments: 90
>Number of distinct parameters to be estimated: 48
>Degrees of freedom (90 - 48): 42
>Result (Default model)
>Minimum was achieved
>Chi-square = -14504178770189,500
>
>
>Many thanks for a reply in advance,
>all the best,
>Nick
>
>
>
>
>
>
http://spssx-discussion.1045642.n5.nabble.com/file/n5713770/Model_standardizedEstimates.
jpg
>
>
>--
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covariance-and-negative-chi-square-value-tp5713770.html
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>
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