> with_seed(seed = 2020, prospective(effect_size = function(x) rnorm(x, 0.3, 0.1),
+ power = 0.8, tl = 0.15, tu = 0.45, B_effect = 10, B = 50))
Message: Truncation could require long computational time

Evaluate n = 501
Estimated power is 1

Evaluate n = 251
Estimated power is 1

Evaluate n = 126
Estimated power is 0.97

Evaluate n = 64
Estimated power is 0.76

Evaluate n = 95
Estimated power is 0.9

Evaluate n = 80
Estimated power is 0.88

Evaluate n = 72
Estimated power is 0.84

Evaluate n = 68
Estimated power is 0.85

Evaluate n = 66
Estimated power is 0.79



	Design Analysis

Hypothesized effect:  rho ~ rnorm(x, 0.3, 0.1) [tl =  0.15 ; tu = 0.45 ]
   n_effect   Min.    1st Qu.   Median   Mean    3rd Qu.   Max.
   10         0.219   0.297     0.326    0.338   0.391     0.43

Study characteristics:
   test_method   sample_n1   sample_n2   alternative   sig_level   df
   pearson       66          NULL        two_sided     0.05        64

Inferential risks:
        Min.    1st Qu.   Median   Mean    3rd Qu.   Max. 
power   0.520   0.71500   0.790    0.778   0.89000   0.960
typeM   0.989   1.07925   1.106    1.144   1.17125   1.464
typeS   0.000   0.00000   0.000    0.000   0.00000   0.000

Critical value(s): rho  =  ± 0.242

