Rashnu is the Zoroastrian deity of truth and justice—the one who
weighs souls on a golden scale.
This R package, developed by Zarathu, draws inspiration from
Rashnu’s role as the divine judge to offer precision and fairness in
sample size determination.
“Where truth is weighed, science begins.”
In clinical trials and research design, every decision matters.
Rashnu helps researchers define the right number of participants
for various statistical tests including: - Non-inferiority studies - Superiority comparisons (Lakatos
method) - One-arm survival designs with transformation-based inference
This package brings clarity, rigor, and justice to your design process.
You can install the stable version of rashnu from CRAN with:
install.packages("rashnu")To access the latest development version, install it from GitHub with:
# install.packages("pak")
pak::pak("zarathucorp/rashnu")Use rashnuBasic() or Click Interactive Sample Size Calculator
Addin
rashnuBasic()
twoSurvSampleSizeNI(
syear = 12,
yrsurv1 = 0.5,
yrsurv2 = 0.5,
alloc = 1,
accrualTime = 24,
followTime = 24,
alpha = 0.025,
power = 0.8,
margin = 1.3
)$Sample_size_of_standard_group
[1] 264
$Sample_size_of_test_group
[1] 264
$Total_sample_size
[1] 528
$Expected_event_numbers_of_standard_group
[1] 227.9
$Expected_event_numbers_of_test_group
[1] 227.9
$Total_expected_event_numbers
[1] 455.9lakatosSampleSize(
syear = 12,
yrsurv1 = 0.3,
yrsurv2 = 0.5,
alloc = 1,
accrualTime = 24,
followTime = 24,
alpha = 0.05,
power = 0.8,
method = "logrank",
side = "two.sided"
)$Sample_size_of_standard_group
[1] 58
$Sample_size_of_test_group
[1] 58
$Total_sample_size
[1] 116
$Expected_event_numbers_of_standard_group
[1] 55.6
$Expected_event_numbers_of_test_group
[1] 49.7
$Total_expected_event_numbers
[1] 105.3
$Actual_power
[1] 0.803oneSurvSampleSize(
survTime = 12,
p1 = 0.3,
p2 = 0.4,
accrualTime = 24,
followTime = 24,
alpha = 0.05,
power = 0.8,
side = "two.sided",
method = "log-log"
)SampleSize Power
189.000 0.802 # 2-Sided Equality
one_mean_size(mu = 2, mu0 = 1.5, sd = 1, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 32
one_mean_size(mu = 2, mu0 = 1.5, sd = 1, alpha = 0.05, n = 32, test_type = "2-side")
[1] 0.8074304
# 1-Sided
one_mean_size(mu = 115, mu0 = 120, sd = 24, alpha = 0.05, beta = 0.2, test_type = "1-side")
[1] 143
one_mean_size(mu = 115, mu0 = 120, sd = 24, alpha = 0.05, n = 143, test_type = "1-side")
[1] 0.8013493
# Non-Inferiority or Superiority
one_mean_size(mu = 2, mu0 = 1.5, delta = -0.5, sd = 1, alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
[1] 7
one_mean_size(mu = 2, mu0 = 1.5, delta = -0.5, sd = 1, alpha = 0.05, n = 7, test_type = "non-inferiority")
[1] 0.8415708
# Equivalence
one_mean_size(mu = 2, mu0 = 2, delta = 0.05, sd = 0.1, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 35
one_mean_size(mu = 2, mu0 = 2, delta = 0.05, sd = 0.1, alpha = 0.05, n = 35, test_type = "equivalence")
[1] 0.810884# 2-Sided Equality
two_mean_size(muA = 5, muB = 10, kappa = 1, sd = 10, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 63
two_mean_size(muA = 5, muB = 10, kappa = 1, sd = 10, alpha = 0.05, nB = 63, test_type = "2-side")
[1] 0.8013024
# 1-Sided
two_mean_size(muA = 132.86, muB = 127.44, kappa = 2, sdA = 15.34, sdB = 18.23, alpha = 0.05, beta = 0.2, test_type = "1-side")
[1] 85
two_mean_size(muA = 132.86, muB = 127.44, kappa = 2, sdA = 15.34, sdB = 18.23, alpha = 0.05, nA = 85, test_type = "1-side")
[1] 0.8020669
# Non-Inferiority or Superiority
two_mean_size(muA = 5, muB = 5, delta = 5, kappa = 1, sd = 10, alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
[1] 50
two_mean_size(muA = 5, muB = 5, delta = 5, kappa = 1, sd = 10, alpha = 0.05, nB = 50, test_type = "non-inferiority")
[1] 0.8037819
# Equivalence
two_mean_size(muA = 5, muB = 4, delta = 5, kappa = 1, sd = 10, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 108
two_mean_size(muA = 5, muB = 4, delta = 5, kappa = 1, sd = 10, alpha = 0.05, nB = 108, test_type = "equivalence")
[1] 0.8045235# 2-Sided Equality
k_mean_size(muA = 5, muB = 10, sd = 10, tau = 1, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 63
k_mean_size(muA = 5, muB = 10, sd = 10, tau = 1, alpha = 0.05, n = 63, test_type = "2-side")
[1] 0.8013024
# 1-Sided
k_mean_size(muA = 132.86, muB = 127.44, kappa = 2, sdA = 15.34, sdB = 18.23, tau = 1, alpha = 0.05, beta = 0.2, test_type = "1-side")
[1] 85
k_mean_size(muA = 132.86, muB = 127.44, kappa = 2, sdA = 15.34, sdB = 18.23, tau = 1, alpha = 0.05, nA = 85, test_type = "1-side")
[1] 0.8020669# 2-Sided Equality
one_prop_size(p = 0.5, p0 = 0.3, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 50
one_prop_size(p = 0.5, p0 = 0.3, alpha = 0.05, n = 50, test_type = "2-side")
[1] 0.8074304
# 1-Sided
one_prop_size(p = 0.05, p0 = 0.02, alpha = 0.05, beta = 0.2, test_type = "1-side")
[1] 191
one_prop_size(p = 0.05, p0 = 0.02, alpha = 0.05, n = 191, test_type = "1-side")
[1] 0.8011562
# Non-inferiority or Superiority
one_prop_size(p = 0.5, p0 = 0.3, delta = -0.1 ,alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
[1] 18
one_prop_size(p = 0.5, p0 = 0.3, delta = -0.1, alpha = 0.05, n = 18, test_type = "non-inferiority")
# Equivalence
[1] 0.8161482
one_prop_size(p = 0.6, p0 = 0.6, delta = 0.2, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 52
one_prop_size(p = 0.6, p0 = 0.6, delta = 0.2, alpha = 0.05, n = 52, test_type = "equivalence")
[1] 0.8060834# 2-Sided Equality
two_prop_size(pA = 0.65, pB = 0.85, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 70
two_prop_size(pA = 0.65, pB = 0.85, kappa = 1, alpha = 0.05, nB = 70, test_type = "2-side")
[1] 0.8019139
# 1-Sided
two_prop_size(pA = 0.65, pB = 0.85, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "1-side")
[1] 55
two_prop_size(pA = 0.65, pB = 0.85, kappa = 1, alpha = 0.05, nB = 55, test_type = "1-side")
[1] 0.8008219
# Non-inferiority or Superiority
two_prop_size(pA = 0.85, pB = 0.65, delta = -0.1, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
[1] 25
two_prop_size(pA = 0.85, pB = 0.65, delta = -0.1, kappa = 1, alpha = 0.05, nB = 25, test_type = "non-inferiority")
[1] 0.8085998
# Equivalence
two_prop_size(pA = 0.65, pB = 0.85, delta = 0.05, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 136
two_prop_size(pA = 0.65, pB = 0.85, delta = 0.05, kappa = 1, alpha = 0.05, nB = 136, test_type = "equivalence")
[1] 0.8033294# 2-Sided Equality
pair_prop_size(p01 = 0.45, p10 = 0.05, alpha = 0.1, beta = 0.1, test_type = "2-side")
[1] 23
pair_prop_size(p01 = 0.45, p10 = 0.05, alpha = 0.1, n = 23, test_type = "2-side")
[1] 0.9023805
# 1-Sided
pair_prop_size(p01 = 0.45, p10 = 0.05, alpha = 0.05, beta = 0.1, test_type = "1-side")
[1] 23
pair_prop_size(p01 = 0.45, p10 = 0.05, alpha = 0.05, n = 23, test_type = "1-side")
[1] 0.9023805k_prop_size(pA = 0.2, pB = 0.4, tau = 2, alpha = 0.05, beta = 0.2)
[1] 96
k_prop_size(pA = 0.2, pB = 0.4, tau = 2, alpha = 0.05, n = 96)
[1] 0.8042732# 2-Sided Equaltiy
coxph_size(hr = 2, hr0 = 1, pE = 0.8, pA = 0.5, alpha = 0.05, beta = 0.2, test_type = "2-side")
[1] 82
coxph_size(hr = 2, hr0 = 1, pE = 0.8, pA = 0.5, alpha = 0.05, n = 82, test_type = "2-side")
[1] 0.8015214
# Non-inferiority or Superiority
coxph_size(hr = 2, hr0 = 1, pE = 0.8, pA = 0.5, alpha = 0.025, beta = 0.2, test_type = "non-inferiority")
[1] 82
coxph_size(hr = 2, hr0 = 1, pE = 0.8, pA = 0.5, alpha = 0.025, n = 82, test_type = "non-inferiority")
[1] 0.8015214
# Equivalence
coxph_size(hr = 1, delta = 0.5, pE = 0.8, pA = 0.5, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 172
coxph_size(hr = 1, delta = 0.5, pE = 0.8, pA = 0.5, alpha = 0.05, n = 172, test_type = "equivalence")
[1] 0.8021573# Equality
or_size(pA = 0.4, pB = 0.25, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "equality")
[1] 156
or_size(pA = 0.4, pB = 0.25, kappa = 1, alpha = 0.05, nB = 156, test_type = "equality")
[1] 0.8020239
# Non-inferiority or Superiority
or_size(pA = 0.4, pB = 0.25, delta = 0.2, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "non-inferiority")
[1] 242
or_size(pA = 0.4, pB = 0.25, delta = 0.2, kappa = 1, alpha = 0.05, nB = 242, test_type = "non-inferiority")
[1] 0.8007201
# Equivalence
or_size(pA = 0.25, pB = 0.25, delta = 0.5, kappa = 1, alpha = 0.05, beta = 0.2, test_type = "equivalence")
[1] 366
or_size(pA = 0.25, pB = 0.25, delta = 0.5, kappa = 1, alpha = 0.05, nB = 366, test_type = "equivalence")
[1] 0.8008593# SCCS, Alt-2
sccs_size(p = 3, r = 42/365, alpha = 0.05, beta = 0.2)
[1] 54
sccs_size(p = 3, r = 42/365, alpha = 0.05, n = 54)
[1] 0.8072004# One Sample Normal
one_norm_size(mu = 2, mu0 = 1.5, sd = 1, alpha = 0.05, beta = 0.2)
[1] 32
one_norm_size(mu = 2, mu0 = 1.5, sd = 1, alpha = 0.05, n = 32)
[1] 0.8074304
# One Sample Binomial
one_bino_size(p = 0.5, p0 = 0.3, alpha = 0.05, beta = 0.2)
[1] 50
one_bino_size(p = 0.5, p0 = 0.3, alpha = 0.05, n = 50)
[1] 0.8074304