[R-sig-eco] Plotting power graph for one sample proportion test

[Paul Johnson]

Hi Kristen,

As an alternative to simulations you could just run pwr.p.test through the data frame suggested by Roman:

library(pwr)
parameters <- 
  expand.grid(
    p.h0 = 0.5, 
    p.h1 = c(0.6, 0.7, 0.8), 
    n = c(50, 100),
    sig.level = c(0.05, 0.01, 0.001))
parameters$h <- ES.h(parameters$p.h1, parameters$p.h0)
parameters

parameters$power <- 
  sapply(1:nrow(parameters), function(i) {
    pwr.p.test(
      h = parameters$h[i],
      n = parameters$n[i],
      sig.level = parameters$sig.level[i])$power
  })
parameters

That just leaves the plotting.

However if you want to use simulations there’s lots of guidance available, including: 
* Chapter 5 of Ben Bolker’s book Ecological Models and Data in R. 
* We have have written an tutorial which covers GLMMs but starts with a simple power.t.test example, in the supplementary info here: dx.doi.org/10.1111/2041-210X.12306

Good luck,
Paul



> On 17 Mar 2016, at 08:27, Roman Luštrik <roman.lustrik at gmail.com> wrote:
> 
> Hi,
> 
> you're looking for a simulation approach of sorts. What I would do is set
> up a data.frame of all combination of parameters (with e.g. `expand.grid`)
> you're interested in and use for example `apply` to go through each
> combination and calculate power. You save that as a new variable and plot
> it.
> 
> If you can provide us with parameters and their ranges perhaps we can be of
> further service.
> 
> Cheers,
> Roman
> 
> On Wed, Mar 16, 2016 at 10:47 PM, Kristen Gorman <kgorman at pwssc.org> wrote:
> 
>> Dear all,
>> I am looking for help in plotting a power analysis using library(pwr).
>> Specifically, I am using the following test:
>> 
>> pwr.p.test ()
>> 
>> I would like to produce a sample size vs power plot for varying alpha
>> levels and differences between the null proportion and alternative
>> proportion.
>> 
>> Thanks for any guidance,
>> Kristen Gorman
>> 
>> 
>> 
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> 
> 
> 
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> 
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