[R] Multiple sets of proportion tests

[Thierry Onkelinx]

Hi anonymous,

?prop.test states that it returns a list. And one of the element is
'p.value'.  str() on the output of prop.test() reveals that too. So
prop.test()$p.value or prop.test()["p.value"] should work.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx op inbo.be
Kliniekstraat 25, B-1070 Brussel
www.inbo.be

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2017-11-24 12:09 GMT+01:00 Allaisone 1 <allaisone1 op hotmail.com>:
>
> Hi all ,
>
>
> I have a dataframe  of 200 columns and 2 rows. The first row in each column contains the frequency of cases in group I . The second row in each column contains the frequency of cases in group II. The frequency of trails is a fixed value for group I(e.g.200) and it is also another fixed values for group II (e.g. 100). The dataset looks like this :-
>
>
>> Mydata
>
>
>                                       variable I      variable II    Variable III  ......... 200
>
> Freq.of cases (gp I)      6493               9375               5524
>
> Freq. of cases (gpII)     509                  462                 54
>
>
>
> The result I need for the first column can be given using this code :
>
>
>  MyResultsI <- prop.test(Mydata$variable I ,c(200,100))
> for the second  column :-
> MyResultsII <- prop.test(Mydata$variable II ,c(200,100))  and so on ..
>
>
> I need to do the analysis for all columns and have only the columns with significant p-value results to be written in the the third row under each column so the final output has to be something like this :-
>
>
>                                       variable I        Variable III  .........
>
> Freq.of cases (gp I)      6493                   5524
>
> Freq. of cases (gpII)     509                      54
>
> p-values                          0.02               0.010
>
> Note, for example, that the 2nd column has bee removed as it resulted in a non-significant p-value result while col 1 and col 3 were included since p-value is less than 0.05.
>
> I'm not sure how to get the p-values only without other details but for the analysis itself , I believe it can be done with apply() function but its not clear to me how to specify the 2nd argument(n=samlpe sizes) in the prop.test.
>
>  MyResults <- apply(Mydata, 2, function(x)prop.test(Mydata,c(200,100))
>
> How can I modify the "n" argument part to solve the issue of non-equivalent length between "x" and "n" ?. How can I modify this further to return only significant p-values results ?. Any help would be very appreciated ..
>
> Regards
>
>         [[alternative HTML version deleted]]
>
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