

Hi,
I have several dependent variables for which I have conducted 2x2x2x2 ANCOVAs with the same IVs and covariate using the GLM command. In several of these ANCOVAs, there are significant 4way interactions that I am trying to interpret. It is my understanding that I should try to tease apart the effects by splitting the file by one of my IVs and working my way down the lower order interactions to see where the effects are.
However, I am lost with regard to the covariate. Should I be trying to see the effects solely at the the mean of the covariate? How can I describe the patterns when they are likely changing at different values of the covariate?
Additionally, is there a reason why SPSS does not test for interactions between the covariate and betweensubject IVs? And how do I interpret an interaction between my withinsubject IVs and my covariate? I have thought about plotting my covariate along the horizontal axis with different lines for the levels of an IV, but this is not as simple as seeing that there are different slopes.
Any advice would be so greatly appreciated!
Jillian
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Hello Jillian. One option would be to use LMATRIX and MMATRIX subcommands,
as shown by Howell & Lacroix (2012).
http://www.tqmp.org/RegularArticles/vol081/p001/p001.pdfBut personally, I find the requirement of generating all those coefficients
offputting, and a likely source of error. Interaction contrasts like this
are much easier to do in Stata, IMO. E.g., the code might look something
like this:
// ANCOVA model with x as continuous covariate
anova y c.x a##b##c##d
// a*b*c interaction at each level of d
contrast a#b#c@d, effects nowald
// a*b interaction for each c*d combination
contrast a#b@c#d, effects nowald
// Effect of a for each b*c*d combination
contrast a@b#c#d, effects nowald
// Etc.
Jon, if you're looking for extension command ideas, something that performs
interaction contrasts like this more easily would be a good one, IMO.
HTH.
Jillian Ma wrote
> Hi,
>
> I have several dependent variables for which I have conducted 2x2x2x2
> ANCOVAs with the same IVs and covariate using the GLM command. In several
> of these ANCOVAs, there are significant 4way interactions that I am
> trying to interpret. It is my understanding that I should try to tease
> apart the effects by splitting the file by one of my IVs and working my
> way down the lower order interactions to see where the effects are.
>
> However, I am lost with regard to the covariate. Should I be trying to see
> the effects solely at the the mean of the covariate? How can I describe
> the patterns when they are likely changing at different values of the
> covariate?
>
> Additionally, is there a reason why SPSS does not test for interactions
> between the covariate and betweensubject IVs? And how do I interpret an
> interaction between my withinsubject IVs and my covariate? I have thought
> about plotting my covariate along the horizontal axis with different lines
> for the levels of an IV, but this is not as simple as seeing that there
> are different slopes.
>
> Any advice would be so greatly appreciated!
>
> Jillian
>
> =====================
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Bruce Weaver
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Thanks, Bruce. This resource seems very helpful to try to tackle the LMATRIX and MMATRIX subcommands. I have still not figured out what to do now with a covariate. I believe I cannot simply look at the interaction at all levels of the covariate because my covariate is a continuous variable. Please let me know if you have any clues on what to do with this covariate.
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Well, the SPSSINC CREATE DUMMIES (Transform > Create Dummy Variables) will create dummy variables and 1, 2, and 3way interaction variables. It can also generate macro names for each set. But it doesn't directly generate the contrast specifications. Hello Jillian. One option would be to use LMATRIX and MMATRIX subcommands,
as shown by Howell & Lacroix (2012).
http://www.tqmp.org/RegularArticles/vol081/p001/p001.pdf
But personally, I find the requirement of generating all those coefficients
offputting, and a likely source of error. Interaction contrasts like this
are much easier to do in Stata, IMO. E.g., the code might look something
like this:
// ANCOVA model with x as continuous covariate
anova y c.x a##b##c##d
// a*b*c interaction at each level of d
contrast a#b#c@d, effects nowald
// a*b interaction for each c*d combination
contrast a#b@c#d, effects nowald
// Effect of a for each b*c*d combination
contrast a@b#c#d, effects nowald
// Etc.
Jon, if you're looking for extension command ideas, something that performs
interaction contrasts like this more easily would be a good one, IMO.
HTH.
Jillian Ma wrote
> Hi,
>
> I have several dependent variables for which I have conducted 2x2x2x2
> ANCOVAs with the same IVs and covariate using the GLM command. In several
> of these ANCOVAs, there are significant 4way interactions that I am
> trying to interpret. It is my understanding that I should try to tease
> apart the effects by splitting the file by one of my IVs and working my
> way down the lower order interactions to see where the effects are.
>
> However, I am lost with regard to the covariate. Should I be trying to see
> the effects solely at the the mean of the covariate? How can I describe
> the patterns when they are likely changing at different values of the
> covariate?
>
> Additionally, is there a reason why SPSS does not test for interactions
> between the covariate and betweensubject IVs? And how do I interpret an
> interaction between my withinsubject IVs and my covariate? I have thought
> about plotting my covariate along the horizontal axis with different lines
> for the levels of an IV, but this is not as simple as seeing that there
> are different slopes.
>
> Any advice would be so greatly appreciated!
>
> Jillian
>
> =====================
> To manage your subscription to SPSSXL, send a message to
> LISTSERV@.UGA
> (not to SPSSXL), with no body text except the
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Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/
"When all else fails, RTFM."
NOTE: My Hotmail account is not monitored regularly.
To send me an email, please use the address shown above.

Sent from: http://spssxdiscussion.1045642.n5.nabble.com/
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hi Jillian, using
/PRINT PARAMETER
subcommand will give you parameter estimates which can help you interpret the impact of the covariate. You may also check the following link for more info on how to interpret them.
hth,
bozena
To: [hidden email]
Subject: Re: Interpreting interactions with covariate
Thanks, Bruce. This resource seems very helpful to try to tackle the LMATRIX and MMATRIX subcommands. I have still not figured out what to do now with a covariate. I believe I cannot simply look at the interaction at all levels of the covariate
because my covariate is a continuous variable. Please let me know if you have any clues on what to do with this covariate.
===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD
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Administrator

Does your model include any interactions involving the covariate? If not,
then the nature of the interactions involving your 4 factor variables does
not depend on the value of the covariate, and should be able to proceed as
shown in the Howell & Lacroix article, /I think/.
Jillian Ma wrote
> Thanks, Bruce. This resource seems very helpful to try to tackle the
> LMATRIX and MMATRIX subcommands. I have still not figured out what to do
> now with a covariate. I believe I cannot simply look at the interaction at
> all levels of the covariate because my covariate is a continuous variable.
> Please let me know if you have any clues on what to do with this
> covariate.
>
> On Fri, Jul 27, 2018 at 9:23 AM, Bruce Weaver <
> bruce.weaver@
> >
> wrote:
>
>> Hello Jillian. One option would be to use LMATRIX and MMATRIX
>> subcommands,
>> as shown by Howell & Lacroix (2012).
>>
>> http://www.tqmp.org/RegularArticles/vol081/p001/p001.pdf>>
>> But personally, I find the requirement of generating all those
>> coefficients
>> offputting, and a likely source of error. Interaction contrasts like
>> this
>> are much easier to do in Stata, IMO. E.g., the code might look something
>> like this:
>>
>> // ANCOVA model with x as continuous covariate
>> anova y c.x a##b##c##d
>> // a*b*c interaction at each level of d
>> contrast a#b#c@d, effects nowald
>> // a*b interaction for each c*d combination
>> contrast a#b@c#d, effects nowald
>> // Effect of a for each b*c*d combination
>> contrast a@b#c#d, effects nowald
>> // Etc.
>>
>>
>> Jon, if you're looking for extension command ideas, something that
>> performs
>> interaction contrasts like this more easily would be a good one, IMO.
>>
>> HTH.
>>
>>
>> Jillian Ma wrote
>> > Hi,
>> >
>> > I have several dependent variables for which I have conducted 2x2x2x2
>> > ANCOVAs with the same IVs and covariate using the GLM command. In
>> several
>> > of these ANCOVAs, there are significant 4way interactions that I am
>> > trying to interpret. It is my understanding that I should try to tease
>> > apart the effects by splitting the file by one of my IVs and working my
>> > way down the lower order interactions to see where the effects are.
>> >
>> > However, I am lost with regard to the covariate. Should I be trying to
>> see
>> > the effects solely at the the mean of the covariate? How can I describe
>> > the patterns when they are likely changing at different values of the
>> > covariate?
>> >
>> > Additionally, is there a reason why SPSS does not test for interactions
>> > between the covariate and betweensubject IVs? And how do I interpret
>> an
>> > interaction between my withinsubject IVs and my covariate? I have
>> thought
>> > about plotting my covariate along the horizontal axis with different
>> lines
>> > for the levels of an IV, but this is not as simple as seeing that there
>> > are different slopes.
>> >
>> > Any advice would be so greatly appreciated!
>> >
>> > Jillian
>> >
>> > =====================
>> > To manage your subscription to SPSSXL, send a message to
>>
>> > LISTSERV@.UGA
>>
>> > (not to SPSSXL), with no body text except the
>> > command. To leave the list, send the command
>> > SIGNOFF SPSSXL
>> > For a list of commands to manage subscriptions, send the command
>> > INFO REFCARD
>>
>>
>>
>>
>>
>> 
>> 
>> Bruce Weaver
>>
> bweaver@
> LISTSERV@.UGA
> (not to SPSSXL), with no body text except the
>> command. To leave the list, send the command
>> SIGNOFF SPSSXL
>> For a list of commands to manage subscriptions, send the command
>> INFO REFCARD
>>
>
> =====================
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Bruce Weaver
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To send me an email, please use the address shown above.

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That makes sense to me. The model does include a significant interaction between the two withinsubject IVs and the covariate. I might be able to explore this with some plotting. I do wonder why by default SPSS does not tell me about any interactions between the betweensubject IVs and the covariate.
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Would you please post your model statement? There’s suddenly appeared two phrases (“significant interaction” and “withinsubject”). Given what you’d posted earlier
I pictured something like this:
GLM y by x1 x2 x3 x4 with cov.
Four between factors with a covariate, all interactions among factors, no factor by covariate interactions.
Gene Maguin
From: SPSSX(r) Discussion <[hidden email]>
On Behalf Of Jillian Ma
Sent: Friday, July 27, 2018 3:01 PM
To: [hidden email]
Subject: Re: Interpreting interactions with covariate
That makes sense to me. The model does include a significant interaction between the two withinsubject IVs and the covariate. I might be able to explore this with some plotting. I do wonder why by default SPSS does not tell me about any
interactions between the betweensubject IVs and the covariate.
On Fri, Jul 27, 2018 at 2:46 PM, Bruce Weaver <[hidden email]> wrote:
Does your model include any interactions involving the covariate? If not,
then the nature of the interactions involving your 4 factor variables does
not depend on the value of the covariate, and should be able to proceed as
shown in the Howell & Lacroix article, /I think/.
Jillian Ma wrote
> Thanks, Bruce. This resource seems very helpful to try to tackle the
> LMATRIX and MMATRIX subcommands. I have still not figured out what to do
> now with a covariate. I believe I cannot simply look at the interaction at
> all levels of the covariate because my covariate is a continuous variable.
> Please let me know if you have any clues on what to do with this
> covariate.
>
> On Fri, Jul 27, 2018 at 9:23 AM, Bruce Weaver <
> [hidden email]
> >
> wrote:
>
>> Hello Jillian. One option would be to use LMATRIX and MMATRIX
>> subcommands,
>> as shown by Howell & Lacroix (2012).
>>
>>
http://www.tqmp.org/RegularArticles/vol081/p001/p001.pdf
>>
>> But personally, I find the requirement of generating all those
>> coefficients
>> offputting, and a likely source of error. Interaction contrasts like
>> this
>> are much easier to do in Stata, IMO. E.g., the code might look something
>> like this:
>>
>> // ANCOVA model with x as continuous covariate
>> anova y c.x a##b##c##d
>> // a*b*c interaction at each level of d
>> contrast a#b#c@d, effects nowald
>> // a*b interaction for each c*d combination
>> contrast a#b@c#d, effects nowald
>> // Effect of a for each b*c*d combination
>> contrast a@b#c#d, effects nowald
>> // Etc.
>>
>>
>> Jon, if you're looking for extension command ideas, something that
>> performs
>> interaction contrasts like this more easily would be a good one, IMO.
>>
>> HTH.
>>
>>
>> Jillian Ma wrote
>> > Hi,
>> >
>> > I have several dependent variables for which I have conducted 2x2x2x2
>> > ANCOVAs with the same IVs and covariate using the GLM command. In
>> several
>> > of these ANCOVAs, there are significant 4way interactions that I am
>> > trying to interpret. It is my understanding that I should try to tease
>> > apart the effects by splitting the file by one of my IVs and working my
>> > way down the lower order interactions to see where the effects are.
>> >
>> > However, I am lost with regard to the covariate. Should I be trying to
>> see
>> > the effects solely at the the mean of the covariate? How can I describe
>> > the patterns when they are likely changing at different values of the
>> > covariate?
>> >
>> > Additionally, is there a reason why SPSS does not test for interactions
>> > between the covariate and betweensubject IVs? And how do I interpret
>> an
>> > interaction between my withinsubject IVs and my covariate? I have
>> thought
>> > about plotting my covariate along the horizontal axis with different
>> lines
>> > for the levels of an IV, but this is not as simple as seeing that there
>> > are different slopes.
>> >
>> > Any advice would be so greatly appreciated!
>> >
>> > Jillian
>> >
>> > =====================
>> > To manage your subscription to SPSSXL, send a message to
>>
>> > [hidden email]
>>
>> > (not to SPSSXL), with no body text except the
>> > command. To leave the list, send the command
>> > SIGNOFF SPSSXL
>> > For a list of commands to manage subscriptions, send the command
>> > INFO REFCARD
>>
>>
>>
>>
>>
>> 
>> 
>> Bruce Weaver
>>
> bweaver@
>>
http://sites.google.com/a/lakeheadu.ca/bweaver/
>>
>> "When all else fails, RTFM."
>>
>> NOTE: My Hotmail account is not monitored regularly.
>> To send me an email, please use the address shown above.
>>
>> 
>> Sent from:
http://spssxdiscussion.1045642.n5.nabble.com/
>>
>> =====================
>> To manage your subscription to SPSSXL, send a message to
>>
> [hidden email]
> (not to SPSSXL), with no body text except the
>> command. To leave the list, send the command
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>> INFO REFCARD
>>
>
> =====================
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Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/
"When all else fails, RTFM."
NOTE: My Hotmail account is not monitored regularly.
To send me an email, please use the address shown above.

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http://spssxdiscussion.1045642.n5.nabble.com/
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About the meaning of parameters and types of contrasts and
corresponding coding  you may want to read
https://stats.stackexchange.com/a/221868/3277
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GLM a1b1 a1b2 a2b1 a2b2 by c d with cov. 2 within factors, 2 between factors and a covariate. Looking at all possible interactions.
Very appreciative of all the help here!
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I think SPSS does not, by default, say anything about interactions between the IVs and the
covariate because that reeks of datadredging.
Looking at interactions, unless it is so that you assert that there weren't any, also tends to
smell of datadredging, especially when you already have 4 main effects. Also, effects of 3rd
order and above tend to be hard to interpret. Moreover, the higher the order, the more likely
that the effect is not replicable  unless it contains a common artifact.
Bad scaling can create interactionartifacts, so I'd check for outliers or other suggestions that
transformation is needed. (Using Ranks is bad for multivariable analyses because that creates
interactions, by artifact.)
Having a mixture of two populations that are too dissimilar can also give you higher order
interactions. In that case, doing separate analyses is often the cure.

Rich Ulrich
That makes sense to me. The model does include a significant interaction between the two withinsubject IVs and the covariate. I might be able to explore this with some plotting. I do wonder why by default SPSS does not tell me about any interactions
between the betweensubject IVs and the covariate.
[snip, rest]
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Administrator

To give the info Gene is asking for, you need to include the complete syntax
for your command. Specifically, you need to show the WSFACTOR, WSDESIGN and
DESIGN subcommands. That should clarify what you mean when you say "all
possible interactions". (I think what you mean by that is all possible
interactions involving the factor variables, but no interactions involving
the covariate.)
The command syntax should be echoed in your output window, so you could copy
from there. Alternatively, exit the GUI dialog via the PASTE button to
generate the syntax.
HTH.
Jillian Ma wrote
> GLM a1b1 a1b2 a2b1 a2b2 by c d with cov.
> 2 within factors, 2 between factors and a covariate. Looking at all
> possible interactions.
>
> Very appreciative of all the help here!
>
> On Fri, Jul 27, 2018 at 3:07 PM, Maguin, Eugene <
> emaguin@
> > wrote:
>
>> Would you please post your model statement? There’s suddenly appeared
>> two
>> phrases (“significant interaction” and “withinsubject”). Given what
>> you’d
>> posted earlier I pictured something like this:
>>
>> GLM y by x1 x2 x3 x4 with cov.
>>
>> Four between factors with a covariate, all interactions among factors, no
>> factor by covariate interactions.
>>
>>
>>
>> Gene Maguin
>>
>>
>>
>> *From:* SPSSX(r) Discussion <
> SPSSXL@.UGA
> > *On Behalf Of *Jillian
>> Ma
>> *Sent:* Friday, July 27, 2018 3:01 PM
>> *To:*
> SPSSXL@.UGA
>> *Subject:* Re: Interpreting interactions with covariate
>>
>>
>>
>> That makes sense to me. The model does include a significant interaction
>> between the two withinsubject IVs and the covariate. I might be able to
>> explore this with some plotting. I do wonder why by default SPSS does not
>> tell me about any interactions between the betweensubject IVs and the
>> covariate.
>>
>>
>>
>> On Fri, Jul 27, 2018 at 2:46 PM, Bruce Weaver <
> bruce.weaver@
> >
>> wrote:
>>
>> Does your model include any interactions involving the covariate? If
>> not,
>> then the nature of the interactions involving your 4 factor variables
>> does
>> not depend on the value of the covariate, and should be able to proceed
>> as
>> shown in the Howell & Lacroix article, /I think/.
>>
>>
>>
>> Jillian Ma wrote
>> > Thanks, Bruce. This resource seems very helpful to try to tackle the
>> > LMATRIX and MMATRIX subcommands. I have still not figured out what to
>> do
>> > now with a covariate. I believe I cannot simply look at the interaction
>> at
>> > all levels of the covariate because my covariate is a continuous
>> variable.
>> > Please let me know if you have any clues on what to do with this
>> > covariate.
>> >
>> > On Fri, Jul 27, 2018 at 9:23 AM, Bruce Weaver <
>>
>> > bruce.weaver@
>>
>> > >
>>
>> > wrote:
>> >
>> >> Hello Jillian. One option would be to use LMATRIX and MMATRIX
>> >> subcommands,
>> >> as shown by Howell & Lacroix (2012).
>> >>
>> >> http://www.tqmp.org/RegularArticles/vol081/p001/p001.pdf>> >>
>> >> But personally, I find the requirement of generating all those
>> >> coefficients
>> >> offputting, and a likely source of error. Interaction contrasts like
>> >> this
>> >> are much easier to do in Stata, IMO. E.g., the code might look
>> something
>> >> like this:
>> >>
>> >> // ANCOVA model with x as continuous covariate
>> >> anova y c.x a##b##c##d
>> >> // a*b*c interaction at each level of d
>> >> contrast a#b#c@d, effects nowald
>> >> // a*b interaction for each c*d combination
>> >> contrast a#b@c#d, effects nowald
>> >> // Effect of a for each b*c*d combination
>> >> contrast a@b#c#d, effects nowald
>> >> // Etc.
>> >>
>> >>
>> >> Jon, if you're looking for extension command ideas, something that
>> >> performs
>> >> interaction contrasts like this more easily would be a good one, IMO.
>> >>
>> >> HTH.
>> >>
>> >>
>> >> Jillian Ma wrote
>> >> > Hi,
>> >> >
>> >> > I have several dependent variables for which I have conducted
>> 2x2x2x2
>> >> > ANCOVAs with the same IVs and covariate using the GLM command. In
>> >> several
>> >> > of these ANCOVAs, there are significant 4way interactions that I am
>> >> > trying to interpret. It is my understanding that I should try to
>> tease
>> >> > apart the effects by splitting the file by one of my IVs and working
>> my
>> >> > way down the lower order interactions to see where the effects are.
>> >> >
>> >> > However, I am lost with regard to the covariate. Should I be trying
>> to
>> >> see
>> >> > the effects solely at the the mean of the covariate? How can I
>> describe
>> >> > the patterns when they are likely changing at different values of
>> the
>> >> > covariate?
>> >> >
>> >> > Additionally, is there a reason why SPSS does not test for
>> interactions
>> >> > between the covariate and betweensubject IVs? And how do I
>> interpret
>> >> an
>> >> > interaction between my withinsubject IVs and my covariate? I have
>> >> thought
>> >> > about plotting my covariate along the horizontal axis with different
>> >> lines
>> >> > for the levels of an IV, but this is not as simple as seeing that
>> there
>> >> > are different slopes.
>> >> >
>> >> > Any advice would be so greatly appreciated!
>> >> >
>> >> > Jillian
>> >> >
>> >> > =====================
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>> >>
>> >>
>> >>
>> >>
>> >>
>> >> 
>> >> 
>> >> Bruce Weaver
>> >>
>>
>> > bweaver@
>>
>> >> http://sites.google.com/a/lakeheadu.ca/bweaver/>> >>
>> >> "When all else fails, RTFM."
>> >>
>> >> NOTE: My Hotmail account is not monitored regularly.
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>> >>
>> >> 
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>> Bruce Weaver
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Ah, I see now, thank you.
Below is the full syntax I used:
GLM mrimp mriip mrbmp mrbip BY readspint sex WITH vscore /WSFACTOR=interest 2 Polynomial difficulty 2 Polynomial /METHOD=SSTYPE(3) /EMMEANS=TABLES(OVERALL) /EMMEANS=TABLES(interest) /EMMEANS=TABLES(difficulty) /EMMEANS=TABLES(sex) /EMMEANS=TABLES(readspint) /EMMEANS=TABLES(interest*difficulty) /EMMEANS=TABLES(sex*interest) /EMMEANS=TABLES(sex*difficulty) /EMMEANS=TABLES(readspint*interest) /EMMEANS=TABLES(readspint*difficulty) /EMMEANS=TABLES(readspint*sex) /EMMEANS=TABLES(sex*interest*difficulty) /EMMEANS=TABLES(readspint*sex*interest) /EMMEANS=TABLES(readspint*sex*difficulty) /EMMEANS=TABLES(readspint*interest*difficulty) /EMMEANS=TABLES(readspint*sex*interest*difficulty) /PRINT=DESCRIPTIVE ETASQ PARAMETER HOMOGENEITY /CRITERIA=ALPHA(.05) /WSDESIGN=interest difficulty interest*difficulty /DESIGN=readspint sex readspint*sex vscore.
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Administrator

Thanks for posting that. One of the drawbacks of using GLM is that it ties
your hands pretty severely as to which terms are included in the model.
That is one reason why it is often preferable to restructure the data from
WIDE to LONG and to then use MIXED to estimate the model. Not only does it
allow you more flexibility re the covariance structure, but it also allows
you complete control over which terms are included in the model. GLM pretty
much ties your hands as to which terms are in the model, as the following
example shows. HTH.
* Get some data for 2x2x2x2 model with repeated measures on the last two
factors.
* Modify path to folder with SPSS sample datasets.
GET FILE='C:\SPSSdata\survey_sample.sav'.
* Let A and B be betweenSs factors.
COMPUTE A = wrkstat EQ 1.
COMPUTE B = marital EQ 1.
FORMATS A B (F1).
DESCRIPTIVES A B.
* Use the 4 education variables (educ paeduc maeduc speduc) for the repeated
measures.
* Use age as the covariate.
COMPUTE X = age.
* Use default settings from the GUI.
GLM educ paeduc maeduc speduc BY A B WITH X
/WSFACTOR=C 2 Polynomial D 2 Polynomial
/WSDESIGN=C D C*D
/DESIGN=X A B A*B.
* BetweenSs effects:
X
A
B
A*B
Error.
* WithinSs effects:
C
C * X < No way to exclude this term
C * A
C * B
C * A * B
Error(C)
D
D * X < No way to exclude this term
D * A
D * B
D * A * B
Error(D)
C * D
C * D * X < No way to exclude this term
C * D * A
C * D * B
C * D * A * B
Error(C*D).
* NOTE that all interactions involving the categorical variables are
included;
* and all interactions of covariate with repeatedmeasures factors are
included.
* There is no way to tell GLM to exclude those interactions.
* We can exclude the C*D and A*B interactions though.
* Remove the twoway interactions from the WSDESIGN & DESIGN subcommands.
GLM educ paeduc maeduc speduc BY A B WITH X
/WSFACTOR=C 2 Polynomial D 2 Polynomial
/WSDESIGN=C D
/DESIGN=X A B.
* BetweenSs effects:
X
A
B
Error.
* WithinSs effects:
C
C * X < No way to exclude this term
C * A
C * B
Error(C)
D
D * X < No way to exclude this term
D * A
D * B
Error(D).
* As shown ablve GLM allows you very little control over which terms
* are included in the model, and no control over interactions of covariates
* with withinSs factors.
* If you restructure the data from WIDE to LONG and use MIXED
* to estimate your model, you will be completely free to determine
* which terms to include in the model.
Jillian Ma wrote
> Ah, I see now, thank you.
>
> Below is the full syntax I used:
>
> GLM mrimp mriip mrbmp mrbip BY readspint sex WITH vscore
> /WSFACTOR=interest 2 Polynomial difficulty 2 Polynomial
> /METHOD=SSTYPE(3)
> /EMMEANS=TABLES(OVERALL)
> /EMMEANS=TABLES(interest)
> /EMMEANS=TABLES(difficulty)
> /EMMEANS=TABLES(sex)
> /EMMEANS=TABLES(readspint)
> /EMMEANS=TABLES(interest*difficulty)
> /EMMEANS=TABLES(sex*interest)
> /EMMEANS=TABLES(sex*difficulty)
> /EMMEANS=TABLES(readspint*interest)
> /EMMEANS=TABLES(readspint*difficulty)
> /EMMEANS=TABLES(readspint*sex)
> /EMMEANS=TABLES(sex*interest*difficulty)
> /EMMEANS=TABLES(readspint*sex*interest)
> /EMMEANS=TABLES(readspint*sex*difficulty)
> /EMMEANS=TABLES(readspint*interest*difficulty)
> /EMMEANS=TABLES(readspint*sex*interest*difficulty)
> /PRINT=DESCRIPTIVE ETASQ PARAMETER HOMOGENEITY
> /CRITERIA=ALPHA(.05)
> /WSDESIGN=interest difficulty interest*difficulty
> /DESIGN=readspint sex readspint*sex vscore.


Bruce Weaver
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