Sample Size Estimation for Bio-Equivalence Trials Through Simulation

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Documentation for package ‘SimTOST’ version 1.1.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

SimTOST-package	Sample Size Estimation via Simulation
.plot_correlation	Plot simulated endpoint correlations
.power_count_joint_serial	Estimate joint power for correlated count endpoints and multiple comparisons
.power_count_serial	Estimate power for count-rate equivalence
as.numeric.simss_mielke	Coerce a Mielke result to a numeric sample size
confint.countpower	Extract the Monte Carlo confidence interval from count power results
confint.countss	Extract the Monte Carlo confidence interval from count power results
confint.simpower	Extract the Monte Carlo confidence interval from fixed-sample-size power results
confint.simss	Confidence Interval for Achieved Power from simss object
get_par	Parameter Configuration for Endpoints and Comparators
plot.countpower	Plot count-outcome power results
plot.countss	Plot count-outcome sample-size results
plot.simpower	Plot fixed-sample-size power results
plot.simpower_curve	Plot fixed-sample-size power results
plot.simss	Plot Power vs Sample Size for Simulation Results
plot.type1error	Plot empirical Type I error
plot.type1error_joint	Plot joint Type I error scenarios
plot_decision_heatmap	Plot simulated decision heatmaps
plot_distribution	Plot distributions of retained simulated observations
plot_mc_error	Plot Monte Carlo error
plot_stability	Plot simulation stability
power_dom	Power Calculation for Difference of Means (DOM) Hypothesis Test
print.countpower	Print count-outcome power results
print.countss	Print count-outcome sample-size results
print.simpower	Print fixed-sample-size power results
print.simss	Print Summary of Sample Size Estimation
print.simss_mielke	Print a Mielke sample-size result
run_simulations	Run a design-specific simulation
run_simulations_2x2_dom	Run Simulations for a 2x2 Crossover Design with Difference of Means (DOM) test
run_simulations_2x2_rom	Run Simulations for a 2x2 Crossover Design with Ratio of Means (ROM) test
run_simulations_par_dom	Run Simulations for a Parallel Design with Difference of Means (DOM) test
run_simulations_par_rom	Run Simulations for a Parallel Design with Ratio of Means (ROM) test
sampleSize	Sample Size Calculation for Bioequivalence and Multi-Endpoint Studies
sampleSize_count	Estimate sample size for count-rate equivalence
sampleSize_count_joint	Estimate sample size for joint correlated count equivalence
sampleSize_Mielke	Sample Size Estimation for Multiple Hypothesis Testing Using Mielke's Method
simParallelEndpoints	Generate Simulated Endpoint Data for Parallel Group Design
simPower	Estimate power at a fixed sample size
SimTOST	Sample Size Estimation via Simulation
summary.countpower	Summarize count-outcome power results
summary.countss	Summary for Count Sample-Size Results
summary.simpower	Summarize fixed-sample-size power results
summary.simss	Summary for Simulation Results
test_2x2_dom	Simulate a 2x2 Crossover Design and Compute Difference of Means (DOM)
test_2x2_rom	Simulate a 2x2 Crossover Design and Compute Ratio of Means (ROM)
test_par_dom	Simulate a Parallel Design and Test Difference of Means (DOM)
test_par_rom	Simulate a Parallel Design and Test Ratio of Means (ROM)
type1Error	Empirical Type I Error at the Least-Favorable Null
update.countpower	Update a standalone count power calculation
update.countss	Update a standalone count sample-size calculation
update.simpower	Update a SimTOST fixed-sample-size power calculation
update.simss	Update a SimTOST sample-size calculation
[.simss_mielke	Preserve named-vector indexing for legacy Mielke examples