[R] Breaking the samplesize package from CRAN

[Bert Gunter]

Suggest you contact the package maintainer.

?maintainer

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Thu, Jul 26, 2018 at 9:49 AM, john matthew via R-help <
r-help using r-project.org> wrote:

> Hello all,
>
> I am using the samplesize package (n.ttest function) to calculate
> number of samples per group power analysis (t-tests with unequal
> variance).
> I can break this n.ttest function from the samplesize package,
> depending on the standard deviations I input.
>
> This works very good.
>
> n.ttest(sd1 = 0.35, sd2 = 0.22 , variance = "unequal")
> # outputs
> $`Total sample size`
> [1] 8
>
> $`Sample size group 1`
> [1] 5
>
> $`sample size group 2`
> [1] 3
>
> Warning message:
> In n.ttest(sd1 = 0.35, sd2 = 0.22, variance = "unequal") :
>   Arguments -fraction- and -k- are not used, when variances are unequal
> The warnings are fine and all is good.
>
>
> But if I run it again with.
> n.ttest(sd1 = 1.68, sd2 = 0.28 , variance = "unequal")
> # outputs
> Error in while (n.start <= n.temp) { :
>   missing value where TRUE/FALSE needed
> In addition: Warning messages:
> 1: In n.ttest(sd1 = 1.68, sd2 = 0.28, variance = "unequal") :
>   Arguments -fraction- and -k- are not used, when variances are unequal
> 2: In qt(conf.level, df = df_approx) : NaNs produced
> 3: In qt(power, df = df_approx) : NaNs produced
>
> It breaks.
> The first obvious thing is that the standard deviations are a lot
> different in the 2nd example that breaks, compared with the first run.
>
> Checking the code myself, I can see it breaks down when the variable
> "df_approx" becomes a negative number, in a while loop from the
> n.ttest function.
> Exert of the code I am talking about.
>
> while (n.start <= n.temp) {
>     n.start <- n1 + n2 + 1
>     n1 <- n.start/(1 + k)
>     n2 <- (k * n.start)/(1 + k)
>     df_approx <- 1/((gamma)^2/(n1 - 1) + (1 - gamma)^2/(n2 - 1))   #
> this calculation becomes negative and breaks subsequently
>     tkrit.alpha <- qt(conf.level, df = df_approx)
>     tkrit.beta <- qt(power, df = df_approx)
>     n.temp <- ((tkrit.alpha + tkrit.beta)^2)/(c^2)
> }
>
> I can hard code df_approx to be an absolute value but I don't know if
> that messes up the statistics.
>
> Can anyone help or any ideas? How to fix?
>
> John.
>
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