On 13 Mar 2001 14:23:04 -0800, [EMAIL PROTECTED] (dennis roberts) wrote:
>well, help me out a bit
>
>i give a survey and ... have categorized respondents into male and females
>... and also into science major and non science majors ... and find a data
>table like:
>
>MTB > chisquare c1 c2
>
>Chi-Square Test: C1, C2
>
>
>Expected counts are printed below observed counts
>
>
> non science science
> C1 C2 Total
>M 1 24 43 67
> 32.98 34.02
>
>F 2 39 22 61
> 30.02 30.98
>
>Total 63 65 128
>
>Chi-Sq = 2.444 + 2.368 +
> 2.684 + 2.601 = 10.097
>DF = 1, P-Value = 0.001
>
>when we evaluate THIS test ... with the chi square test statistic we use in
>THIS case ... in what sense would this be considered to be a TWO tailed
>test?
Yes.
> would we still be using say ... the typical value of .05 to make a
>decision to retain or reject?
Yes most often. But as in any other case investigator is free to
choese a lesser value.
> would we be asking the tester to look up both
>lower and upper CVs from a chi square distribution with 1 df ... and really
>ask him/her to consider rejecting if the obtained chi squared value is
>smaller than the lower CV?
No
>in this case ... minitab is finding the area ABOVE 10.097 in a chi square
>distribution with 1 df ... and recording it as the P value ...
This is the right way to do. Yet I must emphasise that looking at one
side of distribution density does not mean the test is one sided.
>of course, in a simple hypothesis test for a single population mean ... like
>
>Test of mu = 31 vs mu not = 31
>
>Variable N Mean StDev SE Mean
>C5 20 28.10 6.71 1.50
>
>Variable 95.0% CI T P
>C5 ( 24.96, 31.24) -1.93 0.068
>
>the p value that is listed is found by taking the area TO THE LEFT of -1.93
>and to the RIGHT of +1.93 in a t distribution with 19 df ... and adding
>them together
If only you had more cases you could test normal distribution. Then
for (-1.93;1.93) p=0.054. Now look at this: 1.93^2=3.72;
P(Khi2>3.72)=0.054.
>>Incidentally my opinion agrees with international harmonisation
>>guidelines. Just dig FDA site to find them. There are half-page
>>additional explanations why one tailed tests with 5% are unacceptable.
>>The result you can not submit a drug for approval based on studies
>>with one tailed 5% rate tests.
>
>agreement with another position is not sufficient evidence to discard the
>notion that one tailed tests can be legitimate in some cases
Sure but you removed my other arguments... In SOME cases one tailed
test may be legitimate. I just do not see any. Some time ago I was
also puzzled why people do not use one tailed test which seem
intuitively obvious for a beguinner.
Now about agreement... It appears that this agreement is an
internationall consensus. In medicine consensus is one of the methods
to elaborate evidency. Although not perfect.
>are you suggesting that the model for drug research is always correct?
What model? Two tailed?
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