Many thanks for your replies, the Hotelling test seems to do a good
job for what I want.
One follow-up question though would be whether it might be even better
to instead use (for both the continuous and the categorical, but
ordered variable) a non-parametric test, like the
Wilcoxon-Mann-Whitney test? Power is not an issue, as our sample is
quite large...
Thanks,
J
On Wed, Jan 27, 2010 at 11:41 AM, Austin Nichols
<[email protected]> wrote:
> Jen Zhen <[email protected]> :
> You've gotten advice on testing equality of means/proportions one by
> one, but let me urge you to do a joint test. Categorical variables
> can be broken into dummy variables (all but one category turned into
> that many dummies), and then you can use -hotelling- to test equality
> of all relevant means (AKA proportions for dummy variables) across
> treatment and control. This is commonly called a test of balance, and
> Hotelling's test can also be done using a regression of a treatment
> dummy on all variables whose means should be equal across groups,
> which suggests natural generalizations using e.g. various robust VCEs:
> http://www.stata.com/statalist/archive/2009-02/msg01191.html
>
> On Wed, Jan 27, 2010 at 10:34 AM, Jen Zhen <[email protected]> wrote:
>> Hi there,
>>
>> I have a summary table with members from (1) the treatment group and
>> (2) the control group of an experiment, and would like to provide for
>> each observable variable a formal test for whether the two sets of
>> people come indeed from the same population. For the continuous normal
>> variables, I am just doing a t-test to test for equality of means, but
>> I'm not fully sure what to do instead for the categorical variables
>> (with more than 2 categories).
>>
>> I found the -csgof- command for a Chi-Square test of whether the
>> proportions of the different categories in one sample correspond to
>> those coming from some hypothesis, but which command would you use to
>> test whether the proportions in the two groups are identical?
>>
>> Thanks,
>> J
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