Offers a short summary of the power_array object, summarizing the range of observed values and the grid evaluated across. ##' See PowerGrid for details
Usage
# S3 method for class 'power_array'
summary(object, ...)Examples
## Define grid of assumptions to study:
sse_pars = list(
n = seq(from = 10, to = 50, by = 20), # sample size
delta = seq(from = 0.5, to = 1.5, by = 0.5), # effect size
sd = seq(.1, 1, .3)) # standard deviation
## Define function that calculates power based on these assumptions:
PowFun <- function(n, delta, sd){
ptt = power.t.test(n = n/2, delta = delta, sd = sd,
sig.level = 0.05)
return(ptt$power)
}
## Evaluate at each combination of assumptions:
powarr = PowerGrid(pars = sse_pars, fun = PowFun, n_iter = NA)
summary(powarr)
#> Object of class: power_array
#>
#> Range of values: [0.1, 1]
#> Evaluated at:
#> n 10, 30, 50
#> delta 0.5, 1, 1.5
#> sd 0.1, 0.4, 0.7, 1