Dear Vito,
Yes, these tests are *similar* in spirit to loglinear models using
either row/col/both scores for the association.
But I'm still looking for something equivalent to give the same results
as SAS with CMH for
non-parametric tests. One advantage of the CMH tests is that for
stratified tables, a largish sample
size is not required in the individual strata, only the total n.
The computations are described in:
http://support.sas.com/onlinedoc/913/getDoc/en/procstat.hlp/freq_sect27.htm
vito muggeo wrote:
Dear Michael,
It sounds as a linear-by-linear loglinear model (and its variants)
which uses scores for one or more variables in the table.. (see
Agresti, 1990, Categorical Data Analysis. I do remember the pages and
I have not the book here..)
If this is the case, you can use standard call to glm(..,
family=poisson) with score variables in the linear predictor. For
instance for a two-way table with ordered variables the
linear-by-linear model is,
glm(freq~factor(x)+factor(y)+I(score.x*score.y), family=poisson)
The CMH test, probably, is the score test of the parameter of
I(score.x*score.y)..
best,
vito
Michael Friendly ha scritto:
In SAS, for a two-way (or 3-way, stratified) table, the CMH option in
SAS PROC FREQ gives
3 tests that take ordinality of the factors into account, for both
variables, just the column variable
or neither. Is there an equivalent in R?
The mantelhaen.test in stats gives something quite different (a test
of conditional independence for
*nominal* factors in a 3-way table).
e.g. I'd like to reproduce:
*-- CMH tests;
proc freq data=sexfun order=data;
weight count;
tables husband * wife / cmh chisq nocol norow;
run;
The FREQ Procedure
Summary Statistics for Husband by Wife
Cochran-Mantel-Haenszel Statistics (Based on Table Scores)
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 10.0142 0.0016
2 Row Mean Scores Differ 3 12.5681 0.0057
3 General Association 9 16.7689 0.0525
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street http://www.math.yorku.ca/SCS/friendly.html
Toronto, ONT M3J 1P3 CANADA
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