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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