post hoc test on interaction SPSS 13.0

[Sebastien-6]

Hello,
I’m doing two way ANOVA with SPSS 13.0. I would like to do post hoc test.
In the post hoc subcommand, I can select my two main factors, but the
interaction is not present. Does anybody know how to make post hoc test on
interaction with SPSS 13.0?
Thanks,
Sébastien.

[Zdaniuk, Bozena]

What do you mean by post-hoc tests for interaction? Do you mean comparing means of factor A separately at each level of Factor B? if yes, then this can be done using   /EMMEANS = TABLES(A*B) COMPARE (A) subcommand when running GLM. Let me know if you need more specific syntax.
Bozena

Bozena Zdaniuk, Ph.D.

University of Pittsburgh

UCSUR, 6th Fl.

121 University Place

Pittsburgh, PA 15260

Ph.: 412-624-5736

Fax: [phone]

email: [hidden email]


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Sebastien
Sent: Wednesday, June 28, 2006 6:28 AM
To: [hidden email]
Subject: post hoc test on interaction SPSS 13.0

Hello,
I'm doing two way ANOVA with SPSS 13.0. I would like to do post hoc test.
In the post hoc subcommand, I can select my two main factors, but the
interaction is not present. Does anybody know how to make post hoc test on
interaction with SPSS 13.0?
Thanks,
Sébastien.

[Sebastien-6]

How can I use the /EMMEANS = TABLES(A*B) COMPARE (A) subcommand? I have
used SPSS for only few weeks and I know nothing about syntax.

[Edward Boadi]

Try This :

GLM Y BY X1 x2
/EMMEANS = TABLES(X1*X2) COMPARE(X1)
/DESIGN.

The output of this includes a parwise comparison table for the dependent variable Y.

Regards.
Edward

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of
Sebastien
Sent: Wednesday, June 28, 2006 1:58 PM
To: [hidden email]
Subject: Re: post hoc test on interaction SPSS 13.0


How can I use the /EMMEANS = TABLES(A*B) COMPARE (A) subcommand? I have
used SPSS for only few weeks and I know nothing about syntax.

[paulandpen]

Sebastien,

First of all, you needed to inform the list serve group that you know nothing about syntax.  Using syntax in spss to a large extent can be done using the paste function.  In order to test interactions in the GLM modelling in spss, you will unfortunately need to use syntax.  Here is a crash course in syntax for use in the glm approach

Please see the link below on how to do this.

http://www.utexas.edu/its/rc/answers/spss/spss50.html

HTH Paul

> Sebastien <[hidden email]> wrote:
>
> How can I use the /EMMEANS = TABLES(A*B) COMPARE (A) subcommand? I have
> used SPSS for only few weeks and I know nothing about syntax.

[Maguin, Eugene]

All,

I have some questions about understanding how ICCs are computed. The context
for my question is multilevel analyses and not ICCs between raters and
items. Peugh and Enders, in a 2005 article on how to use the spss Mixed
command for several simple types of analyses, compute the ICC as the ratio
of the intercept variance to the sum of the intercept and residual (within
subject) variances. (Every computation in this email is for an unconditional
means model.) My estimate is .000326.

I was also googling ICC and found a different definition. That one is that
ICC is [MS(between) minus MS(error)] divided by [MS(between) plus
MS(error)]. This formula was developed for unordered pairs such as would be
found in a twin study. Using the values from a oneway run This estimate is
.134. (Unianova with the 'by' variable declared as random gives the same
component values.)

I also ran Varcomp and the error variance matches the Mixed residual
variance number but the numerator printed .000, which is probably ok because
the Mixed estimate of the intercept variance is .0003.

I quite confused because, no doubt, there's something I don't understand. I
hope that someone can set me straight because I want to make some analytical
decision on the basis of the (correct) ICC value.

Thanks, Gene Maguin

[Gushta, Matthew]

gene--
a good description of ICCs can be found here:
http://www.uvm.edu/~dhowell/StatPages/More_Stuff/icc/icc.html
specifically, this derivation applies to your question:
http://www.uvm.edu/~dhowell/StatPages/More_Stuff/icc/icc.ht12.gif

your first equation is:
[var(intercept)]/[SUM(var(intercept)) + var(residual)]  (1)

while your second equation is:
[MS(between) - MS(error)]/[MS(between) + MS(error)]     (2)

we see that the relationship between these is based on:
MS(between) = k*var(between) + var(residual)
        where k = number of levels of your "factor" or number of
observations (i.e., time points in a multilevel model).

...these are essentially two approaches to the same problem. typically,
ICCs are used to answer the question of "what proportion of variance is
accounted for by X?". therefore, for hand-calculation and ease of
interpretation, i use (1). the results are easily described in terms of
the original question. and it requires easily-accessed variance
components for calculation.

good luck!

--matthew

* * * * * * * * * * * * * * * * * * * *
matthew m. gushta -- research associate
computer & statistical sciences center
american institutes for research
[hidden email] -- 202.403.5079


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Gene Maguin
Sent: Thursday, July 06, 2006 5:04 PM
To: [hidden email]
Subject: Intraclass correlation (ICC) confusion

All,

I have some questions about understanding how ICCs are computed. The
context for my question is multilevel analyses and not ICCs between
raters and items. Peugh and Enders, in a 2005 article on how to use the
spss Mixed command for several simple types of analyses, compute the ICC
as the ratio of the intercept variance to the sum of the intercept and
residual (within
subject) variances. (Every computation in this email is for an
unconditional means model.) My estimate is .000326.

I was also googling ICC and found a different definition. That one is
that ICC is [MS(between) minus MS(error)] divided by [MS(between) plus
MS(error)]. This formula was developed for unordered pairs such as would
be found in a twin study. Using the values from a oneway run This
estimate is .134. (Unianova with the 'by' variable declared as random
gives the same component values.)

I also ran Varcomp and the error variance matches the Mixed residual
variance number but the numerator printed .000, which is probably ok
because the Mixed estimate of the intercept variance is .0003.

I quite confused because, no doubt, there's something I don't
understand. I hope that someone can set me straight because I want to
make some analytical decision on the basis of the (correct) ICC value.

Thanks, Gene Maguin