Package: SimTOST 1.0.2

Thomas Debray

SimTOST: Sample Size Estimation for Bio-Equivalence Trials Through Simulation

Sample size estimation for bio-equivalence trials is supported through a simulation-based approach that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints. Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability, and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987) <doi:10.1007/BF01068419>, Mielke et al. (2018) <doi:10.1080/19466315.2017.1371071>, Shieh (2022) <doi:10.1371/journal.pone.0269128>, and Sozu et al. (2015) <doi:10.1007/978-3-319-22005-5>. Comprehensive documentation and vignettes guide users through implementation and interpretation of results.

Authors:Thomas Debray [aut, cre], Johanna Munoz [aut], Dewi Amaliah [ctb], Wei Wei [ctb], Marian Mitroiu [ctb], Scott McDonald [ctb], Biogen Inc [cph, fnd]

SimTOST_1.0.2.tar.gz
SimTOST_1.0.2.tar.gz(r-4.5-noble)SimTOST_1.0.2.tar.gz(r-4.4-noble)
SimTOST_1.0.2.tgz(r-4.4-emscripten)SimTOST_1.0.2.tgz(r-4.3-emscripten)
SimTOST.pdf |SimTOST.html
SimTOST/json (API)
NEWS

# Install 'SimTOST' in R:
install.packages('SimTOST', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/smartdata-analysis-and-statistics/simtost/issues

Pkgdown site:https://smartdata-analysis-and-statistics.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

openblascpp

3.54 score 7 scripts 31 exports 5 dependencies

Last updated 1 days agofrom:190307baae. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 19 2025
R-4.5-linux-x86_64OKFeb 19 2025

Exports:check_equivalencederive_allocation_ratederive_arm_namesderive_endpoint_namesderive_varcov_listget_parinfo_msgmcsapplyplot.simsspower_calpower_dompower_Mielkeprint.simssptvptvdfrun_simulations_2x2_domrun_simulations_2x2_romrun_simulations_par_domrun_simulations_par_romsampleSizesampleSize_Mielkesign_MielkesimParallelEndpointstest_2x2_domtest_2x2_romtest_par_domtest_par_romtest_studiesuniroot.integer.modvalidate_positive_definitevalidate_sample_size_limits

Dependencies:data.tableMASSmatrixcalcRcppRcppArmadillo

Bioequivalence Tests for 2x2 Cross-Over Trial Designs with Log-Normal Data

Rendered fromsampleSize_crossover.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Bioequivalence Tests for Parallel Trial Designs with Log-Normal Data

Rendered fromsampleSize_parallel.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Bioequivalence Tests for Parallel Trial Designs: 2 Arms, 1 Endpoint

Rendered fromsampleSize_parallel_2A1E.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Bioequivalence Tests for Parallel Trial Designs: 2 Arms, 3 Endpoints

Rendered fromsampleSize_parallel_2A3E.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Bioequivalence Tests for Parallel Trial Designs: 3 Arms, 1 Endpoint

Rendered fromsampleSize_parallel_3A1E.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Bioequivalence Tests for Parallel Trial Designs: 3 Arms, 3 Endpoints

Rendered fromsampleSize_parallel_3A3E.Rmdusingknitr::rmarkdownon Feb 19 2025.

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Introduction

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