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.
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 at 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. > > ______________________________________________ > 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. >[[alternative HTML version deleted]]
Dear Bert, Thanks for your answer, I already wrote to the maintainer/author of samplesize, Ralph Scherer, on Thu, Apr 19, 2018 but still have no answer. Does anyone have any ideas? Thank you. John. On 26 July 2018 at 20:18, Bert Gunter <bgunter.4567 at gmail.com> wrote:> 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 at 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. >> >> ______________________________________________ >> 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. > >