Practically Important Effect Sizes
pies(
data = NULL,
controlCol = NULL,
expCol = NULL,
d = NULL,
cer = NULL,
r = 1,
n = NULL,
threshold = NULL,
mean = 0,
sd = 1,
bootstrapA = FALSE,
conf.level = 0.95
)
Optionally, if you want to get A, a data frame.
Optionally, if you want to get A, the names of the columns with control and experimental data.
Cohen's d.
The control even rate (see nnt()
).
Arguments for the nnt()
function.
The sample size.
Whether to use bootstrapping to compute A.
The confidence level of confidence intervals.
A dataframe with all values.
pies(d = .5, n = 100, cer = .2, threshold = 2);
#> Warning: 'x' has been rounded to integer: Mean relative difference: 0.01263596
#> Warning: 'x' has been rounded to integer: Mean relative difference: 0.01263596
#> NNT NNT_from_ARR NNT_lo NNT_hi ARR ARR_lo ARR_hi
#> 1 6.012579 -5.882353 -3.778891 -13.26751 -0.17 -0.2646279 -0.07537209
#> CLES U3
#> 1 63.81632 69.14625