absent rows

[cherylscott02]

Is there a way to force SPSS descriptive stats like freq and crosstabs to display all possible values of a given variable, even if there are zero occurrences of the value for the subset of cases being used?  (similar to the "Show items with no data" setting for a pivot table in Excel)
 
 
Cheryl Scott
IR Data Manager
Office of Institutional Research
Truckee Meadows Community College
[hidden email]
[phone] (w)

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[ViAnn Beadle]

Custom Tables and Chart Builder will do this for you provided that you have
defined value labels for the absent values. Otherwise, search the archives
for solutions involving small weights applied to added records contain the
absent values.

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Cheryl Scott
Sent: Thursday, June 12, 2008 9:55 AM
To: [hidden email]
Subject: absent rows

Is there a way to force SPSS descriptive stats like freq and crosstabs to
display all possible values of a given variable, even if there are zero
occurrences of the value for the subset of cases being used?  (similar to
the "Show items with no data" setting for a pivot table in Excel)


Cheryl Scott
IR Data Manager
Office of Institutional Research
Truckee Meadows Community College
[hidden email]
[phone] (w)

=======
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[Richard Ristow]

At 11:54 AM 6/12/2008, Cheryl Scott wrote:

>Is there a way to force SPSS descriptive stats like freq and
>crosstabs to display all possible values of a given variable, even
>if there are zero occurrences of the value for the subset of cases being used?

As ViAnn Beadle wrote, you can use small weight values. It requires
generating and using a dataset with all the values and tiny weights.
Like this (not tested), using an INPUT PROGRAM. (Don't save the
resulting file, though.)

INPUT PROGRAM.
.  NUMERIC DummyWgt (F7.4).

*  'Occupation' takes values 1 through 7  .
.  LOOP Occupation = 1 TO 7.
.     END CASE.
.  END LOOP.

.  'Education'  takes values 1 through 5  .
.  LOOP Education  = 1 TO 5.
.     END CASE.
.  END LOOP.

*  Etc., as necessary or desired          .
END FILE.
END INPUT PROGRAM.
COMPUTE DummyWgt = 1E-4.

ADD FILES
    /FILE=*
    /FILE=RealData.

RECODE DummyWgt (SYSMIS = 1).
WEIGHT BY DummyWgt.

*  And you should be set to go.

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[Hideko Bassett]

Hi,
I'm using AMOS to compare fitness of 3-factor and 2-factor models. Our
theoretically based model consists of 3 factors. By holding one of the
covariances between 2 latent variables (setting it as "1"), I believe
I can create 2-factor model nested in 3-factor model. Then, there 2
reference variables (set regression weight as "1") in the combined
latent variables (one reference variable per latent variable). My
question is that when I hold one of the covariances, do I have to
change regression weight of one reference variables? I'm wondering if
by holding the covariance between 2 latent variables is the same as
one latent variable, then, there shouldn't be 2 reference variables in
it. So I tried to run analysis on this 2-factor model in two different
way. One is to leave 2 reference variables as they are, and the other
is to release one of the reference variables. The two results I got
were dramatically different (the first one had chi-square = 85 and
significant, and the latter one had chi-square = 21 and not
significant).

As you can see, I'm vary new to the world of SEM and AMOS, so any help
would be appreciated.

Also, our data is not normally distributed, so I would like to get
robust chi-square, but I'm not sure how to do it with AMOS. Does
anyone have suggestions on which estimation method to use with non-
normally distributed data?

Thank you very much.
Hideko

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[Swank, Paul R]

Holding the covariance between factors at 1 only works if the factors
(latents) are standardized because otherwise you have to fix the
covariance to the square root of the product of the variances. But if
you standardize the latents then you do not need to set a reference
variable. You may want to subscribe to the SEMNET list as there the
responses are all about SEM.

Paul R. Swank, Ph.D.
Professor and Director of Research
Children's Learning Institute
University of Texas Health Science Center - Houston


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Hideko Bassett
Sent: Thursday, June 12, 2008 12:24 PM
To: [hidden email]
Subject: Comparing 2-factor and 3-factor models

Hi,
I'm using AMOS to compare fitness of 3-factor and 2-factor models. Our
theoretically based model consists of 3 factors. By holding one of the
covariances between 2 latent variables (setting it as "1"), I believe
I can create 2-factor model nested in 3-factor model. Then, there 2
reference variables (set regression weight as "1") in the combined
latent variables (one reference variable per latent variable). My
question is that when I hold one of the covariances, do I have to
change regression weight of one reference variables? I'm wondering if
by holding the covariance between 2 latent variables is the same as
one latent variable, then, there shouldn't be 2 reference variables in
it. So I tried to run analysis on this 2-factor model in two different
way. One is to leave 2 reference variables as they are, and the other
is to release one of the reference variables. The two results I got
were dramatically different (the first one had chi-square = 85 and
significant, and the latter one had chi-square = 21 and not
significant).

As you can see, I'm vary new to the world of SEM and AMOS, so any help
would be appreciated.

Also, our data is not normally distributed, so I would like to get
robust chi-square, but I'm not sure how to do it with AMOS. Does
anyone have suggestions on which estimation method to use with non-
normally distributed data?

Thank you very much.
Hideko

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=====================
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