Thanks Nick,
The treatments are ethinly estradiol (EE) 20mcg v EE 30 mcg and response is
weight change, so I think your first response was right. Is that so?
Paul
On 11/11/02 5:15 pm, "Nick Cox" <[email protected]> wrote:
> I replied to Paul O'Brien
>>>
>>> I have not been able to get the table layout right to do a
>>> test for trend
>>> (NPTREND) with the following data:
>>>
>>> WEIGHT EE20mcg EE30mcg
>>> gained 48 24
>>> stable 210 114
>>> lost 38 18
>>>
>>> What I get is this:
>>>
>>> . tabi 48 24\210 114\38 18
>>>
>>> | col
>>> row | 1 2 | Total
>>> -----------+----------------------+----------
>>> 1 | 48 24 | 72
>>> 2 | 210 114 | 324
>>> 3 | 38 18 | 56
>>> -----------+----------------------+----------
>>> Total | 296 156 | 452
>>>
>>> Pearson chi2(2) = 0.2483 Pr = 0.883
>>>
>>> . list
>>>
>>> row col pop
>>> 1. 1 1 48
>>> 2. 1 2 24
>>> 3. 2 1 210
>>> 4. 2 2 114
>>> 5. 3 1 38
>>> 6. 3 2 18
>>>
>>> . nptrend row, by(col)
>>>
>>> col score obs sum of ranks
>>> 1 1 3 10.5
>>> 2 2 3 10.5
>>>
>>> z = 0.00
>>> Prob > |z| = 1.00
>>>
>>>
>>>
>>> The correct answer is:
>>> One sided P = .2965
>>> Two sided P = .593
>>>
>>> Where am I going wrong?
>>
>> The problem is that Stata does not
>> know that it should look at your -pop- variable.
>>
>> Try
>>
>> . nptrend pop, by(row)
>>
>> Incidentally, a graph created with
>>
>> . ordplot row [w=pop] , by(col)
>>
>> supports the idea that these groups
>> of responses are similar.
>>
>> (For -ordplot-, type -ssc desc ordplot-.)
>>
>
> No, I think my advice here on -nptrend-
> is wrong: I followed your previous
> path too readily. In fact, it
> is not at all clear that this
> is a problem for -nptrend- at
> all. Your response appears
> to be (ordered) categorical
> and your covariate something
> on two levels.
>
> I think the graph still makes sense
> and it suggest that there is no
> relationship worth talking about.
>
> Nick
> [email protected]
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