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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