R help - Aug 2020 - Can I use "mcnemar.test" for 3*3 tables (or is there a bug in the command?)

>2) The second one is to produce a 3 by 3 table, with the rows indicating
>what the kids answered to setting 1 of the experiment, and the columns
>indicating the kids answers to setting 2.
>Now the question is:
>was there marginal homogenity? if not, then that is an indicator that the
>general response to the experimental settings was different for the kids.
>1) can I use "mcnemar.test" for 3*3 (or more) tables ?
As Peter Dalgaard and jchavez12 (on Nabble) pointed out,
"mcnemar.test" does McNemar-Bowker test (Bowker's test) which
tests
symmetry, not marginal homogeneity.
Marginal homogeneity and symmetry are equivalent in 2x2 matrices but
not for larger tables.
I also was confused because many resources (for example Wikipedia
accessed 2020-08-30) introduce McNemar's test as a test of marginal
homogeneity (which it is only for 2x2 matrices).
The R Reference Manual entry for mcnemar.test states that it tests for symmetry.
The code for mcnemar.test is also consistent with the McNemar-Bowker
test for symmetry.
>Is there a bug in the command?
Since the function does what the manual states it does, I would not
call this a bug.
Although, I would like it if the result of mcnemar.test would print
"McNemar's Chi-squared test of symmetry" rather than just
"McNemar's
Chi-squared test."
>Is the one necessarily better then the other? (for example for
>sparser matrices ?)
mcnemar.test often fails for sparse matrices, because symmetric zeros
produce a NaN due to division by zero in the following line of
mcnemar.test code:
STATISTIC <- sum(y[upper.tri(x)]^2/x[upper.tri(x)])
The McNemar-Bowker test uses Chi-squared approximation, which would
not be good for small counts (and sparse matrices).
mcnemar.test does not perform continuity correction for matrices
larger than 2x2.
Is there an exact test for symmetry of matrices larger than 2x2?
I could not find one.
>Is there a bug in the command?
I would not call this a bug.
This behavior of giving "NA" due to a division by zero seems to be
consistent across statistical tests in R.
For example chisq.test(matrix(c(0, 0, 1, 2), nrow = 2) gives NA.
>So which one is "right" ?
You have the option of the McNemar-Bowker test for symmetry
(mcnemar.test), and Stuart-Maxwell test (mh_test).
As an "indicator that the general response to the experimental
settings was different for the kids,"
I would think that if marginal homogeneity is rejected, the two tests
are not equivalent.
I would run mh_test with distribution = "exact" .
The relationship between symmetry and equivalence of two tests is not
as clear to me.
I suppose if the two experimental settings are equivalent and the
distribution of random error for each test are also the same the
resulting matrix would be symmetric?

R 4.0.2 . coin 1.3.1 .

> On 30 Aug 2020, at 20:11 , Kyungmin Ko <kaymin.ko at gmail.com>
wrote:
> 
>> 2) The second one is to produce a 3 by 3 table, with the rows
indicating
>> what the kids answered to setting 1 of the experiment, and the columns
>> indicating the kids answers to setting 2.
>> Now the question is:
>> was there marginal homogenity? if not, then that is an indicator that
the
>> general response to the experimental settings was different for the
kids.
> 
>> 1) can I use "mcnemar.test" for 3*3 (or more) tables ?
> As Peter Dalgaard and jchavez12 (on Nabble) pointed out,
Um, that was on July 19, 2009.....
> "mcnemar.test" does McNemar-Bowker test (Bowker's test) which
tests
> symmetry, not marginal homogeneity.
> Marginal homogeneity and symmetry are equivalent in 2x2 matrices but
> not for larger tables.
> I also was confused because many resources (for example Wikipedia
> accessed 2020-08-30) introduce McNemar's test as a test of marginal
> homogeneity (which it is only for 2x2 matrices).
> The R Reference Manual entry for mcnemar.test states that it tests for
symmetry.
> The code for mcnemar.test is also consistent with the McNemar-Bowker
> test for symmetry.
> 
>> Is there a bug in the command?
> Since the function does what the manual states it does, I would not
> call this a bug.
> Although, I would like it if the result of mcnemar.test would print
> "McNemar's Chi-squared test of symmetry" rather than just
"McNemar's
> Chi-squared test."
> 
>> Is the one necessarily better then the other? (for example for
>> sparser matrices ?)
> mcnemar.test often fails for sparse matrices, because symmetric zeros
> produce a NaN due to division by zero in the following line of
> mcnemar.test code:
> STATISTIC <- sum(y[upper.tri(x)]^2/x[upper.tri(x)])
> The McNemar-Bowker test uses Chi-squared approximation, which would
> not be good for small counts (and sparse matrices).
> mcnemar.test does not perform continuity correction for matrices
> larger than 2x2.
> Is there an exact test for symmetry of matrices larger than 2x2?
> I could not find one.
The exact test for the 2x2 case is isomorphic to a binomial test of the two
off-diagonal elements (conditioning on the sum).

The natural way of constructing a test for the k x k case would be based on the
Cartesian product of k(k-1)/2 binomials with p=.5, (one for each
i,j-combination). This shouldn't be too hard if k is small, but of course it
explodes combinatorially as k increases.

-pd
> 
>> Is there a bug in the command?
> I would not call this a bug.
> This behavior of giving "NA" due to a division by zero seems to
be
> consistent across statistical tests in R.
> For example chisq.test(matrix(c(0, 0, 1, 2), nrow = 2) gives NA.
> 
>> So which one is "right" ?
> You have the option of the McNemar-Bowker test for symmetry
> (mcnemar.test), and Stuart-Maxwell test (mh_test).
> As an "indicator that the general response to the experimental
> settings was different for the kids,"
> I would think that if marginal homogeneity is rejected, the two tests
> are not equivalent.
> I would run mh_test with distribution = "exact" .
> The relationship between symmetry and equivalence of two tests is not
> as clear to me.
> I suppose if the two experimental settings are equivalent and the
> distribution of random error for each test are also the same the
> resulting matrix would be symmetric?
> 
> R 4.0.2 . coin 1.3.1 .
> 
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com