Date: Thu, 2 Feb 2012 17:39:22 -0800
Reply-To: Bruce Weaver <bruce.weaver@hotmail.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Bruce Weaver <bruce.weaver@hotmail.com>
Subject: Re: 2x2 Latin square design analysis help
In-Reply-To: <CAMMWLD1vOtiXYuhYFyOAqFK1ej5wyy+EgZtA3W+BTn_XiWM9dg@mail.gmail.com>
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But as David noted, the 4 conditions are formed by the 2x2 combination of two
binary variables. With the usual coding (i.e., 1 = Yes, 0 = No):
D E Description
---------------------
0 0 Control
1 0 Diet, No Exercise
0 1 Exercise, No Diet
1 1 Diet and Exercise
If the outcome variable was measured at both baseline and followup, then the
preferred approach, arguably, would be a 2x2 ANCOVA, which is equivalent to
an ordinary least squares regression model as follows:
Y1 = b0 + b1*Y0 + b2*D + b3*E + b4*D*E + error
where
Y1 = outcome variable at followup
Y0 = outcome variable at baseline
D and E are as shown above, and D*E = their product.
Of course one /could/ run this model using MIXED, but for users not familiar
with MIXED (and I get the impression the OP is not), it will be much easier
to run it via UNIANOVA (Analyze - GLM - Univariate, with D and E entered as
"fixed factors", and Y0 as a "covariate", and the D*E interaction included).
Another important question David raised (and I don't recall seeing an
answer) is whether there was random assignment to the 4 cells.
There's my two cents!
R B wrote
>
> From what I can tell, you have one between-subjects variable (Condition)
> which has four levels (Diet, Exercise, Diet+Exercise, Control) and one
> within-subjects variable (Time) which has two levels (baseline,
> post-intervention). This is commonly referred to as a mixed ANOVA (not to
> be confused with the MIXED procedure). You could analyze your data by
> fitting a general linear model or linear mixed model in SPSS. I don't have
> time to write code for you at the moment, but quite frankly, there must be
> numerous SPSS examples online. Bottom line is that you need to take into
> account correlation among residuals obtained by repeated observations of
> each subject. You can write specific contrasts of interest using the
> appropriate subcommand. I am always in favor of using the subcommand which
> requires that you understand the coefficient (L) matrix.
>
> Ryan
>
> On Thu, Feb 2, 2012 at 12:08 PM, Sur1605 <surabhi1605@> wrote:
>
>> Thanks David for such an amazing description. This is exactly how i tried
>> doing it before i posted my question on this forum. But everytime i
>> analysed
>> my data somehow it gave me this message:
>> "Post hoc tests are not performed for Diet because there are fewer than
>> three groups.
>> Post hoc tests are not performed for Ex because there are fewer than
>> three
>> groups."
>>
>> Basically its not able to perform the posthoc analysis. I thought i was
>> doing something wrong in feeding in the data in the spreadsheet.
>>
>> And yes, i measured the same variables before and after the trial. Looks
>> like i will have to reconsider the choice of test being used here.
>>
>> Thanks a lot for your help.
>>
>> Sb
>>
>>
>>
>> --
>> View this message in context:
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>> Sent from the SPSSX Discussion mailing list archive at Nabble.com.
>>
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-----
--
Bruce Weaver
bweaver@lakeheadu.ca
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 e-mail, please use the address shown above.
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View this message in context: http://spssx-discussion.1045642.n5.nabble.com/2x2-Latin-square-design-analysis-help-tp5446710p5452480.html
Sent from the SPSSX Discussion mailing list archive at Nabble.com.
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