Package index

All functions

empirical_power_result()

Create an Empirical Power Result object

format(<power_single_rate>)

Format method for power_single_rate class

is.empirical_power_result()

Check if an object is a sim_power_result

multp()

Calculate the Multivariate Normal Probability

multz()

Calculate the Upper Equicoordinate Point of a Multivariate Normal Distribution

power_best_binomial()

Power to Correctly Select the Best Group in a Binomial Test

power_best_normal()

Power calculation for the Indifferent-zone approach for normal outcomes

power_single_rate()

Detectable Event Rate with Specified Power and Sample Size

print(<empirical_power_result>)

Print method for empirical_power_result

print(<power_single_rate>)

Print method for class power_single_rate

prophr()

Calculate Event Probability in the Experimental Group Given a Hazard Ratio

sim_power_best_bin_rank()

Simulate Power to Rank the Best Group Using Binomial Outcomes

sim_power_best_binomial()

Simulate Power to Select the Best Group Using Binomial Outcomes

sim_power_best_norm_rank()

Simulate Power to Select Best Group by Ranks (Normal Outcomes)

sim_power_best_normal()

Simulate Power to Select Best Group (Normal Outcomes)

sim_power_equivalence_normal()

Empirical Power for Equivalence (Normal Outcomes)

sim_power_nbinom()

Empirical Power for Negative Binomial Comparison

sim_power_ni_normal()

Empirical Power for Non-Inferiority (Normal Outcomes)

ss_best_binomial()

Sample Size to Select the Best Group in a Binomial Test

ss_best_normal()

Sample Size for Selecting the Best Treatment in a Normal Response (Indifference-Zone)

ss_ni_ve()

Sample Size and Non-Inferiority Margin for Vaccine Efficacy Trials

tidy(<empirical_power_result>)

Tidy Method for empirical_power_result

wcs_power_best_binomial()

Worst‐Case Scenario Power for the Best Binomial Group