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BayesianQDM - Bayesian Quantitative Decision-Making Framework for Binary and Continuous Endpoints

Provides comprehensive methods to calculate posterior probabilities, posterior predictive probabilities, and Go/NoGo/Gray decision probabilities for quantitative decision-making under a Bayesian paradigm in clinical trials. The package supports both single and two-endpoint analyses for binary and continuous outcomes, with controlled, uncontrolled, and external designs. For single continuous endpoints, three calculation methods are available: numerical integration (NI), Monte Carlo simulation (MC), and Moment-Matching approximation (MM). For two continuous endpoints, a bivariate Normal-Inverse-Wishart conjugate model is implemented with MC and MM methods. For two binary endpoints, a Dirichlet-multinomial model is implemented. External designs incorporate historical data through power priors using exact conjugate representations (Normal-Inverse-Chi-squared for single continuous, Normal-Inverse-Wishart for two continuous, and Dirichlet for binary endpoints), enabling closed-form posterior computation without Markov chain Monte Carlo (MCMC) sampling. This approach significantly reduces computational burden while preserving complete Bayesian rigor. The package also provides grid-search functions to find optimal Go and NoGo thresholds that satisfy user-specified operating characteristic criteria for all supported endpoint types and study designs. S3 print() and plot() methods are provided for all decision probability classes, enabling formatted display and visualisation of Go/NoGo/Gray operating characteristics across treatment scenarios. See Kang, Yamaguchi, and Han (2026) <doi:10.1080/10543406.2026.2655410> for the methodological framework.

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bayesian-statisticsclinical-trialsposterior-predictiveposterior-probabilitypower-priorquantitative-decision-making

5.60 score 6 scripts 556 downloads

FastSurvival - Fast Survival Analysis and Simulation for Clinical Trials

Provides fast alternatives to standard survival analysis functions in the 'survival' package, together with tools for time-to-event trial simulation and sequential analysis. The estimation and testing functions cover a single-time-point Kaplan-Meier estimator (survfit_fast()), log-rank tests including weighted and stratified variants (survdiff_fast()), a closed-form hazard ratio estimator based on the Pike-Halley Estimator method (coxph_fast()), restricted mean survival time (rmst_fast()), milestone survival comparison (milestone_fast()), the max-combo test (maxcombo_fast()), the robust modestly-weighted log-rank test (rmw_fast()), the average hazard with survival weight (ahsw_fast()), and the Kalbfleisch-Prentice average hazard ratio (ahr_fast()). The simulation layer generates individual patient data (simdata_fast()), performs interim or sequential analyses (analysis_fast()), and aggregates operating characteristics (simsummary_fast()). All functions are designed for repeated evaluation inside large simulation loops, such as adaptive sample-size re-estimation, probability-of-success calculations, and regional consistency evaluation in multi-regional trials. Core computations are implemented in 'C++' via 'Rcpp' for maximum performance. Methodological background is described in Collett (2014, ISBN:9780429196294).

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clinical-trialssurvival-analysistime-to-eventcpp

5.28 score 16 scripts 152 downloads

bbssr - Blinded Sample Size Re-Estimation for Binary Endpoints

Provides comprehensive tools for blinded sample size re-estimation (BSSR) in two-arm clinical trials with binary endpoints. Unlike traditional fixed-sample designs, BSSR allows adaptive sample size adjustments during trials while maintaining statistical integrity and study blinding. Implements five exact statistical tests: Pearson chi-squared, Fisher exact, Fisher mid-p, Z-pooled exact unconditional, and Boschloo exact unconditional tests. Supports restricted, unrestricted, and weighted BSSR approaches with exact Type I error control. Statistical methods based on Mehrotra et al. (2003) <doi:10.1111/1541-0420.00051> and Kieser (2020) <doi:10.1007/978-3-030-49528-2_21>.

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binary-endpointsclinical-trialspower-calculationsample-size-calculation

5.28 score 2 stars 16 scripts 175 downloads

twoCoprimary - Sample Size and Power Calculation for Two Co-Primary Endpoints

Comprehensive functions to calculate sample size and power for clinical trials with two co-primary endpoints. The package supports five endpoint combinations: two continuous endpoints (Sozu et al. 2011 <doi:10.1080/10543406.2011.551329>), two binary endpoints using asymptotic methods (Sozu et al. 2010 <doi:10.1002/sim.3972>) and exact methods (Homma and Yoshida 2025 <doi:10.1177/09622802251368697>), mixed continuous and binary endpoints (Sozu et al. 2012 <doi:10.1002/bimj.201100221>), and mixed count and continuous endpoints (Homma and Yoshida 2024 <doi:10.1002/pst.2337>). All methods appropriately account for correlation between endpoints and provide both sample size and power calculation capabilities.

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clinical-trialsco-primarypower-calculationsample-size-calculation

5.26 score 126 downloads

SingleArmMRCT - Regional Consistency Probability for Single-Arm Multi-Regional Clinical Trials

Provides functions to calculate and visualise the Regional Consistency Probability (RCP) for single-arm multi-regional clinical trials (MRCTs) using the Effect Retention Approach (ERA). Six endpoint types are supported: continuous, binary, count (negative binomial), time-to-event via hazard ratio, milestone survival, and restricted mean survival time (RMST). For each endpoint, both a closed-form (or semi-analytical) solution and a Monte Carlo simulation approach are implemented. Two consistency evaluation methods are available: Method 1 (effect retention in Region 1 relative to the overall population) and Method 2 (simultaneous positive effect across all regions). Plotting functions generate faceted visualisations of RCP as a function of the regional allocation proportion, overlaying formula and simulation results for direct comparison. The methodology follows the Japanese MHLW guidelines for MRCTs. Abbreviations used: RCP (Regional Consistency Probability), MRCT (Multi-Regional Clinical Trial), RMST (Restricted Mean Survival Time), MHLW (Ministry of Health, Labour and Welfare).

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binaryclinical-trialscontinuousnegative-binomialregional-consistencytime-to-event

4.48 score 245 downloads

simFastBOIN - Fast Bayesian Optimal Interval Design for Phase I Dose-Finding Trials

Conducting Bayesian Optimal Interval (BOIN) design for phase I dose-finding trials. 'simFastBOIN' provides functions for pre-computing decision tables, conducting trial simulations, and evaluating operating characteristics. The package uses vectorized operations and the Iso::pava() function for isotonic regression to achieve efficient performance while maintaining full compatibility with BOIN methodology. Version 1.3.2 adds p_saf and p_tox parameters for customizable safety and toxicity thresholds. Version 1.3.1 fixes Date field. Version 1.2.1 adds comprehensive 'roxygen2' documentation and enhanced print formatting with flexible table output options. Version 1.2.0 integrated C-based PAVA for isotonic regression. Version 1.1.0 introduced conservative MTD selection (boundMTD) and flexible early stopping rules (n_earlystop_rule). Methods are described in Liu and Yuan (2015) <doi:10.1111/rssc.12089>.

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clinical-trialsdose-findingoncology-trialsphase1

4.30 score 1 stars 131 downloads

RegionalConsistency - Calculate Regional Consistency Probabilities for Multi-Regional Clinical Trials

Provides methods to calculate approximate regional consistency probabilities using Method 1 and Method 2 proposed by the Japanese Ministry of Health, Labor and Welfare (2007) <https://www.pmda.go.jp/files/000153265.pdf>. These methods are useful for assessing regional consistency in multi-regional clinical trials. The package can calculate unconditional, joint, and conditional regional consistency probabilities. For technical details, please see Homma (2024) <doi:10.1002/pst.2358>.

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clinical-trialsregional-consistencyregulatory

3.18 score 1 stars 3 scripts 537 downloads