[R] exact trend test (enumerate all possible contingency tables with fixed row and column margins)
li li
hannah.hlx at gmail.com
Thu Jan 7 19:18:54 CET 2016
I did check the coin package before. I did not see a function in that
package that can be used to list all the possible contingency tables with
fixed margins.
Of course I googled "exact trend test using R". There is not enough help
there.
For up to three groups, I can easily enumerate all the contingency table
with fixed margins, but with 5 groups it is not that easy.
But as mentioned before, this is done implicitly and routinely in
fisher.test function in R. So if anyone who have done this in R before,
please help.
Thanks.
Hanna
2016-01-07 12:20 GMT-05:00 Michael Dewey <lists at dewey.myzen.co.uk>:
> You received a number of suggestions about where to look and packages that
> might be suitable. Did you do that? If you did which ones did you look at
> and why did you reject them?
>
>
> On 07/01/2016 16:29, li li wrote:
>
>> Thanks for all the reply. Below is the data in a better format.
>>
>> addmargins(dat)
>>>
>>
>> dose 0 dose 0.15 dose 0.5 dose 1.5 dose 5 Sum
>>
>> yes 4 3 4 5 8 24
>>
>> no 4 5 4 3 0 16
>>
>> Sum 8 8 8 8 8 40
>>
>> I think it is easier and better that I rephrase my question. I would like
>> to enumerate all possible
>> contingency tables with the row margins and column margins fixed as in the
>> above table. Yes. In fisher's exact test, this should have been done
>> internally. But I need explicitly find all such tables. Need some help on
>> this and thanks very much in advance.
>>
>> Hanna
>>
>>
>> 2016-01-07 7:15 GMT-05:00 peter dalgaard <pdalgd at gmail.com>:
>>
>>
>>> On 07 Jan 2016, at 08:31 , David Winsemius <dwinsemius at comcast.net>
>>> wrote:
>>>
>>>
>>>>> On Jan 6, 2016, at 8:16 PM, li li <hannah.hlx at gmail.com> wrote:
>>>>>
>>>>> Hi all,
>>>>> Is there an R function that does exact randomization trend test?
>>>>> For example, consider the 2 by 5 contingency table below:
>>>>>
>>>>> dose0 dose 0.15 dose 0.5 dose 1.5 dose 5
>>>>> row
>>>>> margin
>>>>> Yes 4 3 4 5
>>>>> 8 24
>>>>> No 4 5 4 3
>>>>> 0 16
>>>>> col sum 8 8 8 8
>>>>> 8 40
>>>>>
>>>>
>>>> Your data presentation has been distorted by your failure to post in
>>>>
>>> plain text. Surely you have been asked in the past to correct this issue?
>>>
>>>>
>>>>
>>>>> To do the exact trend test, we need to enumerate all the contingency
>>>>>
>>>> table
>>>
>>>> with the
>>>>> row and column margins fixed.
>>>>>
>>>>
>>>> Er, how should that be done? A trend test? What is described above would
>>>>
>>> be a general test of no association rather than a trend test. Please use
>>> clear language and be as specific as possible if you choose to respond.
>>>
>>>>
>>>> Find the probability corresponding to
>>>>> obtaining
>>>>> the corresponding contingency tables based on the multivariate
>>>>> hypergeometric distribution. Finally the pvalue is obtained by adding
>>>>> relevant probabilities.
>>>>>
>>>>
>>>> If there is a trend under consideration, then I do not understand such a
>>>>
>>> trend would be modeled under a hypergeometric distribution? A
>>> hypergeometic
>>> distribution would suggest no trend, at least to my current
>>> understanding.
>>>
>>> I'd expect that there is such a beast as a noncentral multivariate
>>> hypergeometric (for the 2x2 case that is what we use to get the CI for
>>> the
>>> odds ratio), but usually, one just wants the null distribution of the
>>> test
>>> statistic.
>>>
>>>
>>>
>>>>
>>>>> Is there an R function that does this? if not, I am wondering whether
>>>>>
>>>> it is
>>>
>>>> possible to
>>>>> enumerate all possible contingency tables that has column sun and row
>>>>>
>>>> sum
>>>
>>>> fixed?
>>>>>
>>>>
>>>> Wel, yes, that is possible and routinely done with `fisher.test`, but it
>>>>
>>> is up to you to describe how that activity leads to a trend test.
>>>
>>>>
>>>> If you assume Poisson distributed errors a trend test is fairly easy to
>>>>
>>> construct with glm.
>>>
>>>>
>>>>
>>> Or, more to the point, there is prop.trend.test(). Neither are exact
>>> tests, though.
>>>
>>> I think package "coin" may something relevant.
>>>
>>> -pd
>>>
>>>
>>> --
>>>> David.
>>>>
>>>>>
>>>>> Thanks very much!!
>>>>>
>>>>> Hanna
>>>>>
>>>>> [[alternative HTML version deleted]]
>>>>>
>>>>> ______________________________________________
>>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide
>>>>>
>>>> http://www.R-project.org/posting-guide.html
>>>
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>
>>>> David Winsemius
>>>> Alameda, CA, USA
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>>
>>> http://www.R-project.org/posting-guide.html
>>>
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>
>>> --
>>> Peter Dalgaard, Professor,
>>> Center for Statistics, Copenhagen Business School
>>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>>> Phone: (+45)38153501
>>> Office: A 4.23
>>> Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
>>>
>>>
>>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
>
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