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Re: iid distribution problem [SEC: UNCLASSIFIED]

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Gosse, Michelle

Re: iid distribution problem [SEC: UNCLASSIFIED]

Hi Frank,

I have the same question as David and Rich, I'm not sure how the IID issue in your subject line relates to the design you've laid out below.

Do you think there is a lack of independence between the ratings given by the various probands?

Can you give a fuller description of the study design?

Cheers
Michelle

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of drfg2008
Sent: Wednesday, 14 September 2011 9:39 PM
To: [hidden email]
Subject: Re: iid distribution problem

the case seems to be a bit more complicated (at least for me). Any help and/or syntax appreciated.

Problem:

"479 raters score 16 objects. Each rater score (a) the same 16 objects"

this is a shortened version of the data with 6 objects and 2 raters...

*caseNo:* number of object
*DV:* dependent variable - has to be explained (object)
*IV1:* 1st independent variable - has to be tested (object)
*IV2:* 2nd independent variable - has to be tested (object)
*IV3:* 3rd independent variable - has to be tested (object)
*probandNo:* the number of the proband (rater)
*prob_age:* age of proband - has to be tested (rater)
*prob_sex:* sex of proband (rater) - has to be tested (rater)

probandNo DV IV1 IV2 IV3 caseNo prob_age prob_sex
1000 1 5 4 3 1 42 1
1000 3 4 1 1 2 42 1
1000 4 5 2 4 3 42 1
1000 2 8 4 5 4 42 1
1000 1 7 3 2 5 42 1
1000 1 2 2 2 6 42 1

1001 1 2 2 2 1 32 2
1001 1 7 3 2 2 32 2
1001 2 8 4 5 3 32 2
1001 4 5 2 4 4 32 2
1001 1 5 4 3 5 32 2
1001 3 4 1 1 6 32 2

The underlying question is which of the variables (object: IV1, IV2, IV3 -
Rater: prob_age, prob_sex) exerts an influence on DV.

Thanks

-----
Dr. Frank Gaeth
FU-Berlin

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Gosse, Michelle

Re: iid distribution problem [SEC: UNCLASSIFIED]

Hi Frank,

Thanks for the earlier response, and I concur with David below.

I'm lost as to the study design, and the fact there are 6 sets of observations per proband makes me wonder if the IV1, IV2, and IV3 were presented using a within-subjects counterbalancing - which would give 6 results per subject.

Cheers
Michelle

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of David Marso
Sent: Friday, 16 September 2011 7:02 AM
To: [hidden email]
Subject: Re: iid distribution problem

Isn't this a repeated measures data set?
Don't see how that is incorporated.
Are you sure all these factors should be fixed (Again we have no idea what IV1, IV2, IV3 are)?
Are you sure you want to waste DF on 3,4 and 5 way interactions?
Do you have any theory guiding this analysis or are you on a GIGO adventure.
Seriously Frank, is some silly NDA preventing you from spilling the beans on WTF the data are all about?

drfg2008 wrote:

>
> never used this procedure before.
>
> Andy Fields "Discovering Statistics using SPSS":
>
>
> MIXED DV BY prob_sex WITH IV1 IV2 IV3 prob_age
> /CRITERIA=CIN(95) MXITER(100) MXSTEP(5) SCORING(1)
> SINGULAR(0.000000000001) HCONVERGE(0,
> ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)
> /FIXED=prob_sex IV1 IV2 IV3 prob_age prob_sex*IV1 prob_sex*IV2
> prob_sex*IV3 prob_sex*prob_age
> IV1*IV2 IV1*IV3 IV1*prob_age IV2*IV3 IV2*prob_age IV3*prob_age
> prob_sex*IV1*IV2 prob_sex*IV1*IV3
> prob_sex*IV1*prob_age prob_sex*IV2*IV3 prob_sex*IV2*prob_age
> prob_sex*IV3*prob_age IV1*IV2*IV3
> IV1*IV2*prob_age IV1*IV3*prob_age IV2*IV3*prob_age
> prob_sex*IV1*IV2*IV3 prob_sex*IV1*IV2*prob_age
> prob_sex*IV1*IV3*prob_age prob_sex*IV2*IV3*prob_age
> IV1*IV2*IV3*prob_age
> prob_sex*IV1*IV2*IV3*prob_age | SSTYPE(3)
> /METHOD=REML
> /PRINT=DESCRIPTIVES.
>

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UNCLASSIFIED

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