Package: RARfreq 0.1.5

RARfreq: Response Adaptive Randomization with 'Frequentist' Approaches

Provides functions and command-line user interface to generate allocation sequence by response-adaptive randomization for clinical trials. The package currently supports two families of frequentist response-adaptive randomization procedures, Doubly Adaptive Biased Coin Design ('DBCD') and Sequential Estimation-adjusted Urn Model ('SEU'), for binary and normal endpoints. One-sided proportion (or mean) difference and Chi-square (or 'ANOVA') hypothesis testing methods are also available in the package to facilitate the inference for treatment effect. Additionally, the package provides comprehensive and efficient tools to allow one to evaluate and compare the performance of randomization procedures and tests based on various criteria. For example, plots for relationship among assumed treatment effects, sample size, and power are provided. Five allocation functions for 'DBCD' and six addition rule functions for 'SEU' are implemented to target allocations such as 'Neyman', 'Rosenberger' Rosenberger et al. (2001) <doi:10.1111/j.0006-341X.2001.00909.x> and 'Urn' allocations.

Authors:Mengjia Yu [aut], Xiu Huang [aut, cre], Li Wang [aut], Hongjian Zhu [aut]

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RARfreq.pdf |RARfreq.html✨
RARfreq/json (API)

# Install 'RARfreq' in R:
install.packages('RARfreq', repos = c('https://hoyden0329.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

18 exports 0.09 score 44 dependencies 2 scripts 915 downloads

Last updated 4 months agofrom:05f4a09455. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-winOKSep 05 2024
R-4.5-linuxOKSep 05 2024
R-4.4-winOKSep 05 2024
R-4.4-macOKSep 05 2024
R-4.3-winOKSep 05 2024
R-4.3-macOKSep 05 2024

Exports:DBCD_BINARYDBCD_BINARY_rawDBCD_GAUSSIANDBCD_GAUSSIAN_rawpower_comparison_Power_vs_npower_comparison_Power_vs_n_GAUSSIANpower_comparison_Power_vs_Trtpower_comparison_Power_vs_Trt_GAUSSIANSEU_BINARY_rawSEU_GAUSSIAN_rawSEU_power_comparison_Power_vs_nSEU_power_comparison_Power_vs_n_GAUSSIANSEU_power_comparison_Power_vs_TrtSEU_power_comparison_Power_vs_Trt_GAUSSIANSEU_simulation_mainSEU_simulation_main_GAUSSIANsimulation_mainsimulation_main_GAUSSIAN

Dependencies:clicolorspacecpp11data.tabledplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatex2explatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepatchworkpillarpkgconfigplyrpurrrR6rbibutilsRColorBrewerRcppRdpackreshape2rlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Doubly Adaptive Biased Coin Design (Binary Responses)DBCD_BINARY
Doubly Adaptive Biased Coin Design (Binary Data Frame)DBCD_BINARY_raw
Doubly Adaptive Biased Coin Design (Gaussian Responses)DBCD_GAUSSIAN
Doubly Adaptive Biased Coin Design (Gaussian Responses)DBCD_GAUSSIAN_raw
Comparison of Powers for Different Tests under Different DBCD Randomization Methods (Binary Responses)power_comparison_Power_vs_n
Comparison of Powers for Different Tests under Different DBCD Randomization Methods (Gaussian Responses)power_comparison_Power_vs_n_GAUSSIAN
Comparison of Powers for Treatment Effects under Different DBCD Randomization Methods (Binary Responses)power_comparison_Power_vs_Trt
Comparison of Powers for Treatment Effects under Different DBCD Randomization methods (Gaussian Responses)power_comparison_Power_vs_Trt_GAUSSIAN
Sequential Estimation-adjusted Urn Model (Binary Data)SEU_BINARY_raw
Sequential Estimation-adjusted Urn Model (Gaussian Responses)SEU_GAUSSIAN_raw
Comparison of Powers for Sample Sizes under Different SEU Randomization Methods (Binary Responses)SEU_power_comparison_Power_vs_n
Comparison of Powers for Sample Sizes under Different SEU Randomization Methods (Gaussian Responses)SEU_power_comparison_Power_vs_n_GAUSSIAN
Comparison of Powers for Treatment Effects under Different SEU Randomization Methods (Binary Responses)SEU_power_comparison_Power_vs_Trt
Comparison of Powers for Treatment Effects under Different SEU Randomization Methods (Gaussian Responses)SEU_power_comparison_Power_vs_Trt_GAUSSIAN
Sequential Estimation-adjusted Urn Model with Simulated Data (Binary Data)SEU_simulation_main
Sequential Estimation-adjusted Urn Model with Simulated Data (Gaussian Responses)SEU_simulation_main_GAUSSIAN
Doubly Adaptive Biased Coin Design with Simulated Data (Binary Responses)simulation_main
Doubly Adaptive Biased Coin Design with Simulated Data (Gaussian Responses)simulation_main_GAUSSIAN