[R] Fisher's Test 5x4 table
paul brett
brettpaul16 at gmail.com
Sun Aug 30 13:54:09 CEST 2015
Hi Gerrit,
I tried both of your suggestions and got the exact same thing.
Fisher's Exact Test for Count Data with simulated p-value (based on 1e+05
replicates)
data: Trapz
p-value = 1e-05
alternative hypothesis: two.sided
I put in a few changes myself based on the details section on what should
be used for a larger than 2x2 table, getting the exact same thing as
before. I have removed or = 1, conf.int = TRUE. Added y = NULL, control =
list(30) and changed simulate.p.value = TRUE.
> fisher.test( Trapz, y = NULL, workspace = 200000, hybrid = TRUE,control =
list(30), simulate.p.value = TRUE, B =1e5)
isher's Exact Test for Count Data with simulated p-value (based on 1e+05
replicates)
data: Trapz
p-value = 1e-05
alternative hypothesis: two.sided
> fisher.test( Trapz, y = NULL, workspace = 200000, hybrid = TRUE,control =
list(30), simulate.p.value = TRUE, B =1e7)
Fisher's Exact Test for Count Data with simulated p-value (based on 1e+07
replicates)
data: Trapz
p-value = 1e-07
alternative hypothesis: two.sided
Dispite these chages, the changes equations is not giving me the results
for the calculations. The changes I have made seem to satisfy what is in
the details section on R, and I don't have the issue of workspace in R.
What I do to get the results of the fisher test?
Is there something simple that I am missing?
Regards,
Paul
On Fri, Aug 28, 2015 at 3:52 PM, Gerrit Eichner <
Gerrit.Eichner at math.uni-giessen.de> wrote:
> Paul,
>
> as the error messages of your first three attempts (see below) tell you -
> in an admittedly rather cryptic way - your table or its sample size,
> respectively, are too large, so that either the "largest (hash table) key"
> is too large, or your (i.e., R's) workspace is too small, or your
> hardware/os cannot allocate enough memory to calculate the p-value of
> Fisher Exact Test exactly by means of the implemented algorithm.
>
> One way out of this is to approximate the exact p-value through
> simulation, but apparently there occurred a typo in your (last) attempt to
> do that (Error: unexpected '>' in ">").
>
>
> So, for me the following works (and it should also for you) and gives the
> shown output (after a very short while):
>
> Trapz <- as.matrix( read.table( "w.txt", head = T, row.names = "Traps"))
>>
>
> set.seed( 20150828) # For the sake of reproducibility.
>> fisher.test( Trapz, simulate.p.value = TRUE,
>>
> + B = 1e5)
>
> Fisher's Exact Test for Count Data with simulated p-value (based on
> 1e+05 replicates)
>
> data: Trapz
> p-value = 1e-05
> alternative hypothesis: two.sided
>
>
>
> Or for a higher value for B if you are patient enough (with a computing
> time of several seconds) :
>
> set.seed( 20150828)
>> fisher.test( Trapz, simulate.p.value=TRUE, B = 1e7)
>>
>
> Fisher's Exact Test for Count Data with simulated p-value (based on
> 1e+07 replicates)
>
> data: Trapz
> p-value = 1e-07
> alternative hypothesis: two.sided
>
>
> Hth -- Gerrit
>
> (BTW, you don't have to specify arguments (in function calls) whose
> default values you don't want to change.)
>
>
>
>
> On Fri, 28 Aug 2015, paul brett wrote:
>
> Hi Gerrit,
>> I spotted that, it was a mistake on my own part, it should
>> read 1.trap.2.barrier. I have corrected it on the file attached.
>>
>> So I have done these so far:
>> > fisher.test(Trapz, workspace = 200000, hybrid = FALSE, control = list(),
>> or = 1, alternative = "two.sided", conf.int = TRUE, conf.level =
>> 0.95,simulate.p.value = FALSE, B = 2000)
>> Error in fisher.test(Trapz, workspace = 2e+05, hybrid = FALSE, control =
>> list(), :
>> FEXACT error 501.
>> The hash table key cannot be computed because the largest key
>> is larger than the largest representable int.
>> The algorithm cannot proceed.
>> Reduce the workspace size or use another algorithm.
>>
>> fisher.test(Trapz, workspace = 2000, hybrid = FALSE, control = list(), or
>>>
>> = 1, alternative = "two.sided", conf.int = TRUE, conf.level =
>> 0.95,simulate.p.value = FALSE, B = 2000)
>> Error in fisher.test(Trapz, workspace = 2000, hybrid = FALSE, control =
>> list(), :
>> FEXACT error 40.
>> Out of workspace.
>>
>>> fisher.test(Trapz, workspace = 1e8, hybrid = FALSE, control = list(), or
>>>
>> = 1, alternative = "two.sided", conf.int = TRUE, conf.level =
>> 0.95,simulate.p.value = FALSE, B = 2000)
>> Error in fisher.test(Trapz, workspace = 1e+08, hybrid = FALSE, control =
>> list(), :
>> FEXACT error 501.
>> The hash table key cannot be computed because the largest key
>> is larger than the largest representable int.
>> The algorithm cannot proceed.
>> Reduce the workspace size or use another algorithm.
>>
>>> fisher.test(Trapz, workspace = 2000000000, hybrid = FALSE, control =
>>>
>> list(), or = 1, alternative = "two.sided", conf.int = TRUE, conf.level =
>> 0.95,simulate.p.value = FALSE, B = 2000)
>> Error: cannot allocate vector of size 7.5 Gb
>> In addition: Warning messages:
>> 1: In fisher.test(Trapz, workspace = 2e+09, hybrid = FALSE, control =
>> list(), :
>> Reached total allocation of 6027Mb: see help(memory.size)
>> 2: In fisher.test(Trapz, workspace = 2e+09, hybrid = FALSE, control =
>> list(), :
>> Reached total allocation of 6027Mb: see help(memory.size)
>> 3: In fisher.test(Trapz, workspace = 2e+09, hybrid = FALSE, control =
>> list(), :
>> Reached total allocation of 6027Mb: see help(memory.size)
>> 4: In fisher.test(Trapz, workspace = 2e+09, hybrid = FALSE, control =
>> list(), :
>> Reached total allocation of 6027Mb: see help(memory.size)
>>
>> fisher.test(Trapz, workspace = 1e8, hybrid = FALSE, control = list(), or =
>> 1, alternative = "two.sided", conf.int = TRUE, conf.level =
>> 0.95,simulate.p.value = TRUE, B = 1e5)
>> Error: unexpected '>' in ">"
>>
>> So the issue could be perhaps that R cannot compute my sample as the
>> workspace needed is too big? Is there a way around this? I think I have
>> everything set out correctly.
>> Is my only other alternative is to do a 2x2 fisher test for each of the
>> variables?
>>
>> I attach on the pdf the Minitab result for the Chi squared test as proof
>> (I
>> know that getting very low p values are highly unlikely but sometimes it
>> happens). Seeing is believing i suppose!
>>
>> Regards,
>> Paul
>>
>>
>>
>> On Fri, Aug 28, 2015 at 8:56 AM, Gerrit Eichner <
>> Gerrit.Eichner at math.uni-giessen.de> wrote:
>>
>> Dear Paul,
>>>
>>> quoting the email-footer: "PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html and provide commented,
>>> minimal, self-contained, reproducible code."
>>>
>>> So, what exactly did you try and what was the actual problem/error
>>> message?
>>>
>>> Besides that, have you noted that two of you data rows have the same
>>> name?
>>>
>>>
>>> Have you read the online help page of fisher.test():
>>>
>>> ?fisher.test
>>>
>>>
>>> Have you tried anything like the following?
>>>
>>> W <- as.matrix( read.table( "w.txt", head = T)[-1])
>>>
>>> fisher.test( W, workspace = 1e8)
>>> # For workspace look at the help page, but it presumably
>>> # won't work because of your sample size.
>>>
>>>
>>> set.seed( 20150828) # for reproducibility
>>> fisher.test( W, simulate.p.value = TRUE, B = 1e5)
>>> # For B look at the help page.
>>>
>>>
>>> Finally: Did Minitab really report "p > 0.001"? ;-)
>>>
>>> Hth -- Gerrit
>>>
>>>
>>> Dear all,
>>>
>>>> I am trying to do a fishers test on a 5x4 table on R
>>>> statistics. I have already done a chi squared test using Minitab on this
>>>> data set, getting a result of (1, N = 165.953, DF 12, p>0.001), yet
>>>> using
>>>> these results (even though they are excellent) may not be suitable for
>>>> publication. I have tried numerous other statistical packages in the
>>>> hope
>>>> of doing this test, yet each one has just the 2x2 table.
>>>> I am struggling to edit the template fishers test on R to fit
>>>> my table (as according to the R book it is possible, yet i cannot get it
>>>> to
>>>> work). The template given on the R documentation and R book is for a 2x2
>>>> fisher test. What do i need to change to get this to work? I have
>>>> attached
>>>> the data with the email so one can see what i am on about. Or do i have
>>>> to
>>>> write my own new code to compute this.
>>>>
>>>> Yours Sincerely,
>>>> Paul Brett
>>>>
>>>>
>>>>
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