Simulating and conducting four phase 12 clinical trials with correlated binary bivariate outcomes described. Uses the 'Efftox' (efficacy and toxicity tradeoff, <https://biostatistics.mdanderson.org/SoftwareDownload/SingleSoftware/Index/2>) and SPSO (Semi-Parametric Stochastic Ordering) models with Utility and Desirability based objective functions for dose finding.

Provides a comprehensive set of tools to simulate, evaluate, and compare model-assisted designs for early-phase (Phase I/II) clinical trials, including:
  - BOIN12 (Bayesian optimal interval phase 1/11 trial design; Lin et al. (2020) <doi:10.1200/PO.20.00257>),
  - BOIN-ET (Takeda, K., Taguri, M., & Morita, S. (2018) <doi:10.1002/pst.1864>),
  - EffTox (Thall, P. F., & Cook, J. D. (2004) <doi:10.1111/j.0006-341X.2004.00218.x>),
  - Ji3+3 (Joint i3+3 design; Lin, X., & Ji, Y. (2020) <doi:10.1080/10543406.2020.1818250>),
  - PRINTE (probability intervals of toxicity and efficacy design; Lin, X., & Ji, Y. (2021) <doi:10.1177/0962280220977009>),
  - STEIN (simple toxicity and efficacy interval design; Lin, R., & Yin, G. (2017) <doi:10.1002/sim.7428>),
  - TEPI (toxicity and efficacy probability interval design; Li, D. H., Whitmore, J. B., Guo, W., & Ji, Y. (2017) <doi:10.1158/1078-0432.CCR-16-1125>),
  - uTPI (utility-based toxicity Probability interval design; Shi, H., Lin, R., & Lin, X. (2024) <doi:10.1002/sim.8922>).
 Includes flexible simulation parameters that allow
 researchers to efficiently compute operating characteristics under
 various fixed and random trial scenarios and export the results.

Implements Bayesian phase I repeated measurement design that 
    accounts for multidimensional toxicity endpoints and longitudinal efficacy 
    measure from multiple treatment cycles. The package provides flags to 
    fit a variety of model-based phase I design, including 1 stage models with
    or without individualized dose modification, 3-stage models with or without
    individualized dose modification, etc. Functions are provided to recommend 
    dosage selection based on the data collected in the available patient cohorts 
    and to simulate trial characteristics given design parameters. 
    Yin, Jun, et al. (2017) <doi:10.1002/sim.7134>.