[R] Re: Yates' correction
Peter Ho
peter at fe.up.pt
Thu Nov 21 19:02:31 CET 2002
Thanks for the reply Frank.
I will in future send these types of questions to sci.stat.consult
Usenet news group, of which I was not previously aware of.
The interersting point about the two results, is the fact that the null
hypothesis is not rejected using Yate's correction, but is rejected
without Yate's correction. at 5% level of significance. I guess this
will be better answered in sci.stat.consult .
Thanks again
Peter
----------------------------
ISR-Porto
Frank E Harrell Jr wrote:
>On Wed, 20 Nov 2002 21:51:56 +0000
>Peter Ho <peter at fe.up.pt> wrote:
>
>
>
>>Dear list readers,
>>
>>This question is concerned with the use of the chisq.test() in R.
>>A test was conducted to determine the difference between 2 samples A and
>>B. Column I consisted of correct and incorrect assessment of 30 matched
>>pairs (AA or BB) , whereas column II consisted of correct and incorrect
>>assessment of 30 unmatched pairs (AB or BA). This example is given in a
>>book on the sensory evaluation techniques. The author's did not use
>>used when analysing a 2x2 contigency table using the chi-square test. I
>>have found conflicting views in literature with some people for and
>>conflicting results.
>>
>> > x <- matrix(c(17, 13, 9, 21), nc = 2)
>> > chisq.test(x,correct = TRUE)
>>
>> Pearson's Chi-squared test with Yates' continuity correction
>>
>>data: x
>>X-squared = 3.3258, df = 1, p-value = 0.0682
>>
>> > chisq.test(x,correct = F)
>>
>> Pearson's Chi-squared test
>>
>>data: x
>>X-squared = 4.3439, df = 1, p-value = 0.03714
>>
>> >
>>
>>The same data analysed using Fisher's exact test is similar to the
>> > fisher.test(x)
>>
>> Fisher's Exact Test for Count Data
>>
>>data: x
>>p-value = 0.06728
>>alternative hypothesis: true odds ratio is not equal to 1
>>95 percent confidence interval:
>> 0.9354766 10.1716022
>>sample estimates:
>>odds ratio
>> 2.992580
>>
>>I suppose looking at the results, the correct conclusion should be taken
>>using the correction for continuity. In fact, the statistics books I
>>example, Nonparametric statistics - Sidney Siegel and John Castellan 1988)
>>
>>I would like to hear anyone's view on this, especially statisticians.
>>
>>
>>Thanks in advance
>>
>>Peter
>>----------------------------------
>>ISR-Porto
>>
>>
>
>In general you use Yates' correction if you want the results to be conservative as with Fisher's "exact" test. I generally use the chi-square test without continuity correction. The price of "exact" tests (those that guarantee the type I error is no greater than a set value) is conservatism. I prefer tests that get closest to the target alpha value even if they exceed it a little bit on occasion.
>
>This kind of question would be slightly more appropriate for the sci.stat.consult Usenet news group.
>
>
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