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Basic functions for power analysis in R

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I'm trying to compute a power curve, and came across this rather off behavior - when providing `d` as a vector, the function fails, but supplying each element of `d`...

For some reason I'm able to specify `alternative = 'greater'` but not `alternative = 'less'` in `pwr.2p.test()`, although it seems to me like both options should be valid and return...

I am wondering whether the d is actually dz rather than cohen'd when the type = c('paired'), because when I assigend the same value to 'effect size dz' in the...

I'm using `pwr` as the basis for the jamovi `jpower` module (https://github.com/richarddmorey/jpower) but I'm having some difficulty with effect size calculations, particularly at low sample sizes. Consider the following code:...

I'm looking at the documentation and the source code for `ES.w2()`. The way the statistic is calculated is quite clear. It is not clear what is the name of that...

In `pwr.t2n.test`, does `alternative = "greater"` mean that the n1 group is greater or the n2 group is greater? Similar questions wherever this argument is used. (This mystery is never...

> pwr.t.test(n=NULL, d=7, sig.level = 0.05, power=0.8) Error in uniroot(function(n) eval(p.body) - power, c(2 + 1e-10, 1e+09)) : f() values at end points not of opposite sign > pwr.t.test(n=NULL, d=7,...

Currently, in the documentation of `pwr.norm.test()`, the effect size argument (i.e. `d=` ) is described as "Effect size d=mu-mu0". However, in the code documentation, you use the standardized effect size:...