SimTOST.RdSimTOST: A Package for Sample Size Simulations
The SimTOST package provides tools for simulating sample sizes, calculating power, and assessing type-I error for various statistical scenarios.
Each function name links to its full help page.
sampleSize: simulation-based sample-size planning
for continuous and count outcomes, including multiple endpoints and
comparator families.
simPower: simulated power for a fixed sample size,
with support for continuous and count-outcome analyses.
sampleSize_Mielke: Mielke et al.'s sample-size
calculation for multiple, correlated hypotheses and k-out-of-m rules.
simParallelEndpoints: generates correlated normal
or log-normal endpoint data for a parallel-group design.
get_par: prepares and validates endpoint,
covariance, allocation, and hierarchy parameters for planning.
run_simulations: dispatches a continuous
simulation to the selected design and test combination.
print.simss (print): prints a concise design, power,
confidence-interval, and sample-size report.
summary.simss (summary): returns and prints a
structured summary of the simulation result.
confint.simss (confint): extracts the stored Monte
Carlo confidence interval for achieved power.
plot.simss (plot): plots simulated power against
sample size with confidence intervals and the target-power line.
update.simss and update.simpower
(update): reruns a result while replacing only explicitly supplied
planning or simulation parameters.
Mielke, J., Jones, B., Jilma, B. & König, F. Sample Size for Multiple Hypothesis Testing in Biosimilar Development. Statistics in Biopharmaceutical Research 10, 39–49 (2018).