If I understand you right, you have several multiple response variables
(with the responses encoded in numeric strings) and you want to see
whether these are associated with sex. To tabulate the data, I would
convert your variables into collections of dummy variables using
regexpr(), then use table(). You can use a modified chi-squared test
with a Rao-Scott correction on the resulting tables; see Thomas and
Decady (2004). Bootstrapping is another possible approach.
@article{,
Author = {Thomas, D. Roland and Decady, Yves J.},
Journal = {International Journal of Testing},
Number = {1},
Pages = {43 - 59},
Title = {Testing for Association Using Multiple Response Survey Data:
Approximate Procedures Based on the Rao-Scott Approach.},
Volume = {4},
Year = {2004},
Url=http://search.ebscohost.com/login.aspx?direct=true&db=pbh&AN=13663214&site=ehost-live
}
Hope this helps,
James
--
James Reilly
Department of Statistics, University of Auckland
Private Bag 92019, Auckland, New Zealand
On 21/9/07 7:14 AM, Birgit Lemcke wrote:
> First thanks for your answer.
> Now I try to explain better:
>
> I have species in the rows and morphological attributes in the
> columns coded by numbers (qualitative variables; nominal and ordinal).
> In one table for the male plants of every species and in the other
> table for the female plants of every species. The variables contain
> every possible occurrence in this species and this gender.
> I would like to compare every variable between male and female plants
> for example using a ChiSquare Test.
> The Null-hypothesis could be: Variable male is equal to variable Female.
>
> The question behind all is, if male and female plants in this species
> are significantly different and which attributes are responsible for
> this difference.
>
> I really hope that this is better understandable. If not please ask.
>
> Thanks a million in advance.
>
>
> Greetings
>
> Birgit
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