Re: MxN variation of McNemar-Bowker test?

Posted by Bruce Weaver on Jan 26, 2018; 1:40pm
URL: http://spssx-discussion.165.s1.nabble.com/MxN-variation-of-McNemar-Bowker-test-tp5735446p5735453.html

If you mean that all 4 categories were available for the first model, but the
4th category just was not used, fair enough.  In that case, I think you can
solve your problem by using INTEGER mode on your CROSSTABS command.  

* McNemar-Bowker test for marginal homogeneity with non-square table.
DATA LIST FREE / res1980 res1985 wt .
BEGIN DATA.
1 1 11607
1 2 100
1 3 366
1 4 124
2 1 87
2 2 13677
2 3 515
2 4 302
3 1 172
3 2 225
3 3 17819
3 4 270
4 1 63
4 2 176
4 3 286
4 4 10192
END DATA.
WEIGHT BY wt.

* Create the symmetry and quasi-symmetry indicator variables .
COMPUTE s1 = any(1,res1980,res1985).
COMPUTE s2 = any(2,res1980,res1985).
COMPUTE s3 = any(3,res1980,res1985).

COMPUTE qs12 = s1*s2 .
COMPUTE qs13 = s1*s3 .
COMPUTE qs14 = s1*any(4,res1980,res1985).
COMPUTE qs23 = s2*s3 .
COMPUTE qs24 = s2*any(4,res1980,res1985).
COMPUTE qs34 = s3*any(4,res1980,res1985).

FORMATS s1 to qs34 (F4).

* Symmetry model - reported in Agresti, page 357 .
GENLOG
res1980 res1985 WITH s1 s2 s3 qs12 qs13 qs14 qs23 qs24 qs34
/PRINT FREQ ESTIM
/PLOT NONE
/DESIGN qs12 qs13 qs14 qs23 qs24 qs34 s1 s2 s3 .

CROSSTABS RES1980 by RES1985 /STATISTICS=MCNEMAR.

* RECODE RES1980 so that all 4s become 3s.
RECODE RES1980 (4=3) (ELSE=COPY) into RES1980r.
* Now redo the CROSSTABS command--but note that we need
* to use INTEGER mode with a non-square table.
CROSSTABS VARIABLES = RES1980r (1,4) RES1985(1,4)
 /TABLES = RES1980r by RES1985 /STATISTICS=MCNEMAR.

* References.
*
http://spssx-discussion.1045642.n5.nabble.com/MxN-variation-of-McNemar-Bowker-test-td5735446.html#a5735452
* http://www-01.ibm.com/support/docview.wss?uid=swg21477019.



rsijben wrote

> Thank you for your suggestions,
>
> Considering how each case is assigned to 1 category per model I created
> the
> following long format:
>
> 1 Column for case/subject number, each case listed twice as we're
> comparing
> 2 models.
> 1 Column listing model number 1 or 2, used as repeated measure.
> 1 Column listing the assigned category for each case by the respective
> model.
>
>
> Inputting this to the multinomial logistic under generalized linear grants
> the error: "Repeated measures analysis is not supported for the
> multinomial
> probability distribution".
>
>
> @Mr. Weaver,
>
> The first model assigns each case to 1 of 3 categories while the 2nd model
> assigns these cases to 4 categories. Model 1 could, for example, assign
> the
> data evenly over the conditions yielding a proportion of 0.33 for each
> category. Model 2, being more optimized, might recognize that half the
> cases
> in category 3 actually belong in a new category 4, creating the
> proportions
> 0.33, 0.33, 0.1565, 0.1565 for categories 1, 2, 3, and 4, respectively.
> The
> proportion of cases assigned to category 1 and 2 would remain identical.
>
>
>
>
>
> --
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Bruce Weaver
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