Other packages > Find by keyword >

trialr  

Clinical Trial Designs in 'rstan'
View on CRAN: Click here


Download and install trialr package within the R console
Install from CRAN:
install.packages("trialr")

Install from Github:
library("remotes")
install_github("cran/trialr")

Install by package version:
library("remotes")
install_version("trialr", "0.1.6")



Attach the package and use:
library("trialr")
Maintained by
Kristian Brock
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-21
Latest Update: 2023-03-12
Description:
A collection of clinical trial designs and methods, implemented in 'rstan' and R, including: the Continual Reassessment Method by O'Quigley et al. (1990) <doi:10.2307/2531628>; EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the two-parameter logistic method of Neuenschwander, Branson & Sponer (2008) <doi:10.1002/sim.3230>; and the Augmented Binary method by Wason & Seaman (2013) <doi:10.1002/sim.5867>; and more. We provide functions to aid model-fitting and analysis. The 'rstan' implementations may also serve as a cookbook to anyone looking to extend or embellish these models. We hope that this package encourages the use of Bayesian methods in clinical trials. There is a preponderance of early phase trial designs because this is where Bayesian methods are used most. If there is a method you would like implemented, please get in touch.
How to cite:
Kristian Brock (2017). trialr: Clinical Trial Designs in 'rstan'. R package version 0.1.6, https://cran.r-project.org/web/packages/trialr. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.0.1 (2017-11-21 16:33), 0.0.2 (2018-08-08 22:40), 0.0.3 (2018-08-09 12:20), 0.0.4 (2018-10-24 23:30), 0.0.5 (2018-11-12 17:40), 0.0.6 (2019-01-17 15:10), 0.0.7 (2019-03-03 18:30), 0.1.0 (2019-04-21 23:00), 0.1.1 (2019-05-25 02:00), 0.1.2 (2019-06-25 13:40), 0.1.3 (2020-01-08 23:30), 0.1.4 (2020-04-06 15:20), 0.1.5 (2020-10-16 01:00)
Other packages that cited trialr R package
View trialr citation profile
Other R packages that trialr depends, imports, suggests or enhances
Complete documentation for trialr
Functions, R codes and Examples using the trialr R package
Some associated functions: as.data.frame.crm_fit . as.data.frame.efftox_fit . as.mcmc.list.crm_fit . as.mcmc.list.efftox_fit . as_tibble.augbin_2t_1a_fit . as_tibble.dose_finding_paths . augbin_2t_1a_fit . augbin_fit . binary_prob_success . careful_escalation . closest_to_target . crm_codified_dose_logistic . crm_dtps . crm_fit-class . crm_params-class . crm_path_analysis . crm_prior_beliefs . crm_process . df_parse_outcomes . dose_finding_fit-class . dose_finding_path_node-class . eff_at_dose . efftox_analysis_to_df . efftox_contour_plot . efftox_dtps . efftox_dtps_to_dataframe . efftox_fit-class . efftox_get_tox . efftox_parameters_demo . efftox_params-class . efftox_parse_outcomes . efftox_path_analysis . efftox_priors . efftox_process . efftox_simulate . efftox_solve_p . efftox_superiority . efftox_utility . efftox_utility_density_plot . get_efftox_priors . n_at_dose . parse_dose_finding_outcomes . parse_eff_tox_dose_finding_outcomes . peps2_get_data . peps2_process . plot.crm_fit . plot.efftox_fit . predict.augbin_2t_1a_fit . print.augbin_fit . print.crm_fit . print.efftox_fit . print.nbg_fit . prior_predictive_augbin_2t_1a . prob_success . prob_tox_exceeds . ranBin2 . rlkjcorr . spread_paths . stan_augbin . stan_augbin_demo . stan_crm . stan_efftox . stan_efftox_demo . stan_hierarchical_response_thall . stan_nbg . stan_peps2 . summary.crm_fit . summary.efftox_fit . total_weight_at_dose . tox_at_dose . trialr-package . trialr_simulate . weights_at_dose . 
Some associated R codes: EffTox.R . augbin_2t_1a_fit.R . augbin_fit.R . binary_prob_success.R . careful_escalation.R . crm_codified_dose_logistic.R . crm_dtps.R . crm_fit.R . crm_params.R . crm_path_analysis.R . crm_prior_beliefs.R . crm_process.R . df_parse_outcomes.R . dose_finding_fit.R . dose_finding_path_node.R . dose_finding_paths.R . eff_at_dose.R . efftox_analysis_to_df.R . efftox_contour_plot.R . efftox_dtps.R . efftox_dtps_to_dataframe.R . efftox_fit.R . efftox_get_tox.R . efftox_parameters_demo.R . efftox_params.R . efftox_parse_outcomes.R . efftox_path_analysis.R . efftox_priors.R . efftox_process.R . efftox_simulate.R . efftox_solve_p.R . efftox_superiority.R . efftox_utility.R . efftox_utility_density_plot.R . get_efftox_priors.R . misc.R . n_at_dose.R . nbg_fit.R . parse_dose_finding_outcomes.R . parse_eff_tox_dose_finding_outcomes.R . peps2_get_data.R . peps2_process.R . prior_predictive_augbin_2t_1a.R . prob_success.R . prob_tox_exceeds.R . ranBin2.R . rlkjcorr.R . spread_paths.R . stan_augbin.R . stan_augbin_demo.R . stan_crm.R . stan_efftox.R . stan_efftox_demo.R . stan_hierarchical_response_thall.R . stan_nbg.R . stan_peps2.R . stanmodels.R . total_weight_at_dose.R . tox_at_dose.R . trialr-package.R . trialr_simulate.R . weights_at_dose.R .  Full trialr package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  
Rfast2  
A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, ...
Download / Learn more Package Citations See dependency  
wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA