# Sample size for `"2-side"` test
one_mean_size(mu = 2, mu0 = 1.5, sd = 1,
alpha = 0.05, beta = 0.2, test_type = "2-side")
# Power of `"2-side"` test
one_mean_size(mu = 2, mu0 = 1.5, sd = 1,
alpha = 0.05, n = 32, test_type = "2-side")
# Sample size for `"1-side"` test
one_mean_size(mu = 115, mu0 = 120, sd = 24,
alpha = 0.05, beta = 0.2, test_type = "1-side")
# Power of `"1-side"` test
one_mean_size(mu = 115, mu0 = 120, sd = 24,
alpha = 0.05, n = 143, test_type = "1-side")
# Sample size for `"non-inferiority"` test
one_mean_size(mu = 2, mu0 = 1.5, delta = -0.5, sd = 1,
alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
# Power of `"non-inferiority"` test
one_mean_size(mu = 2, mu0 = 1.5, delta = -0.5, sd = 1,
alpha = 0.05, n = 7, test_type = "non-inferiority")
# Sample size for `"equivalence"` test
one_mean_size(mu = 2, mu0 = 2, delta = 0.05, sd = 0.1,
alpha = 0.05, beta = 0.2, test_type = "equivalence")
# Power of `"equivalence"` test
one_mean_size(mu = 2, mu0 = 2, delta = 0.05, sd = 0.1,
alpha = 0.05, n = 35, test_type = "equivalence")
Run the code above in your browser using DataLab