[R] Kruskal-Wallace power calculations.

Collin Lynch cflynch at ncsu.edu
Fri Apr 3 23:17:40 CEST 2015


Thank you very much Greg, I will give that a try.

    Best,
    Collin.

On Fri, Apr 3, 2015 at 1:43 PM, Greg Snow <538280 at gmail.com> wrote:
> Here is some sample code:
>
> ## Simulation function to create data, analyze it using
> ## kruskal.test, and return the p-value
> ## change rexp to change the simulation distribution
>
> simfun <- function(means, k=length(means), n=rep(50,k)) {
>   mydata <- lapply( seq_len(k), function(i) {
>     rexp(n[i], 1) - 1 + means[i]
>   })
>   kruskal.test(mydata)$p.value
> }
>
> # simulate under the null to check proper sizing
> B <- 10000
> out1 <- replicate(B, simfun(rep(3,4)))
> hist(out1)
> mean( out1 <= 0.05 )
> binom.test( sum(out1 <= 0.05), B, p=0.05)
>
> ### Now simulate for power
>
> B <- 10000
> out2 <- replicate(B, simfun( c(3,3,3.2,3.3)))
> hist(out2)
> mean( out2 <= 0.05 )
> binom.test( sum(out2 <= 0.05), B, p=0.05 )
>
> This simulates from a continuous exponential (skewed) and shifts to
> get the means (shifted location is a common assumption, though not
> required for the actual test).
>
> On Thu, Apr 2, 2015 at 8:19 PM, Collin Lynch <cflynch at ncsu.edu> wrote:
>> Thank you Jim, I did see those (though not my typo :) and am still
>> pondering the warning about post-hoc analyses.
>>
>> The situation that I am in is that I have a set of individuals who
>> have been assigned a course grade.  We have then clustered these
>> individuals into about 50 communities using standard community
>> detection algorithms with the goal of determining whether community
>> membership affects one of their grades.  We are using the KW test as
>> the grade data is strongly non-normal and my coauthors preferred KW as
>> an alternative.
>>
>> The two issues that I am struggling with are: 1) whether the post-hoc
>> power analysis would be useful; and 2) how to code the simulation
>> studies that are described in:
>> http://onlinelibrary.wiley.com/doi/10.1002/bimj.4710380510/abstract
>>
>>
>> Problem #1 is of course beyond the scope of this e-mail list though I
>> would welcome anyone's suggestions on that point.  I am not sure that
>> I buy the arguments against it offered here:
>>
>> http://graphpad.com/support/faq/why-it-is-not-helpful-to-compute-the-power-of-an-experiment-to-detect-the-difference-actually-observed-why-is-post-hoc-power-analysis-futile/
>>
>> It seems that the rationale boils down to "you didn't find it so you
>> couldn't find it" but that does not tell me how far off I was from the
>> goal.  I am still perusing the articles the author cites however.
>>
>>
>> With respect to question #2 I am trying to lay my hands on the article
>> and did find this old r-help discussion:
>> http://r.789695.n4.nabble.com/Power-of-Kruskal-Wallis-Test-td4671188.html
>> however I am not sure how to adapt the simulation studies that it
>> links to to my current problem.  The links it leads to focus on
>> mixed-effects models.  This may be more of a pure stats question and
>> not suited for this list but I thought I'd ask in the hopes that
>> anyone had any more specific KW code or knew of a good tutorial for
>> the right kinds of simulation studies.
>>
>>     Thank you,
>>     Collin.
>>
>>
>>
>>
>> On Thu, Apr 2, 2015 at 6:35 PM, Jim Lemon <drjimlemon at gmail.com> wrote:
>>> Hi Collin,
>>> Have a look at this:
>>>
>>> http://stats.stackexchange.com/questions/70643/power-analysis-for-kruskal-wallis-or-mann-whitney-u-test-using-r
>>>
>>> Although, thinking about it, this might have constituted your "perusal of
>>> the literature".
>>>
>>> Plus it always looks better when you spell the names properly
>>>
>>> Jim
>>>
>>>
>>> On Fri, Apr 3, 2015 at 2:23 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
>>> wrote:
>>>>
>>>> Please stop... you are acting like a broken record, and are also posting
>>>> in HTML format. Please read the Posting Guide and demonstrate that you have
>>>> used a search engine on this topic before posting again.
>>>>
>>>> ---------------------------------------------------------------------------
>>>> Jeff Newmiller                        The     .....       .....  Go
>>>> Live...
>>>> DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.       ##.#.  Live
>>>> Go...
>>>>                                       Live:   OO#.. Dead: OO#..  Playing
>>>> Research Engineer (Solar/Batteries            O.O#.       #.O#.  with
>>>> /Software/Embedded Controllers)               .OO#.       .OO#.
>>>> rocks...1k
>>>>
>>>> ---------------------------------------------------------------------------
>>>> Sent from my phone. Please excuse my brevity.
>>>>
>>>> On April 2, 2015 7:25:20 AM PDT, Collin Lynch <cflynch at ncsu.edu> wrote:
>>>> >Greetings, I am working on a project where we are applying the
>>>> >Kruskal-Wallace test to some factor data to evaluate their correlation
>>>> >with
>>>> >existing grade data.  I know that the grade data is nonnormal therefore
>>>> >we
>>>> >cannot rely on ANOVA or a similar parametric test.  What I would like
>>>> >to
>>>> >find is a mechanism for making power calculations for the KW test given
>>>> >the
>>>> >nonparametric assumptions.  My perusal of the literature has suggested
>>>> >that
>>>> >a simulation would be the best method.
>>>> >
>>>> >Can anyone point me to good examples of such simulations for KW in R?
>>>> >And
>>>> >does anyone have a favourite package for generating simulated data or
>>>> >conducting such tests?
>>>> >
>>>> >    Thank you,
>>>> >    Collin.
>>>> >
>>>> >       [[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.
>>>>
>>>> ______________________________________________
>>>> 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.
>>>
>>>
>>
>> ______________________________________________
>> 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.
>
>
>
> --
> Gregory (Greg) L. Snow Ph.D.
> 538280 at gmail.com



More information about the R-help mailing list