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psborrow2 (version 0.0.4.0)

Bayesian Dynamic Borrowing Analysis and Simulation

Description

Bayesian dynamic borrowing is an approach to incorporating external data to supplement a randomized, controlled trial analysis in which external data are incorporated in a dynamic way (e.g., based on similarity of outcomes); see Viele 2013 for an overview. This package implements the hierarchical commensurate prior approach to dynamic borrowing as described in Hobbes 2011 . There are three main functionalities. First, 'psborrow2' provides a user-friendly interface for applying dynamic borrowing on the study results handles the Markov Chain Monte Carlo sampling on behalf of the user. Second, 'psborrow2' provides a simulation framework to compare different borrowing parameters (e.g. full borrowing, no borrowing, dynamic borrowing) and other trial and borrowing characteristics (e.g. sample size, covariates) in a unified way. Third, 'psborrow2' provides a set of functions to generate data for simulation studies, and also allows the user to specify their own data generation process. This package is designed to use the sampling functions from 'cmdstanr' which can be installed from .

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Install

install.packages('psborrow2')

Monthly Downloads

148

Version

0.0.4.0

License

Apache License 2.0

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Repository

https://github.com/Genentech/psborrow2

Homepage

https://genentech.github.io/psborrow2/index.html

Maintainer

Matt Secrest

Last Published

February 12th, 2025

Functions in psborrow2 (0.0.4.0)

DataSimCutOff-class

Covariates-class

Covariate Class

MCMCSimulationResult-class

MCMCSimulationResult Class

Outcome class

PriorGamma-class

PriorGamma Class

OutcomeSurvPEM-class

OutcomeSurvPEM Class

DataSimEvent-class

Event Time Distribution Object

OutcomeSurvExponential-class

OutcomeSurvExponential Class

OutcomeSurvWeibullPH-class

OutcomeSurvWeibullPH Class

OutcomeContinuousNormal-class

OutcomeContinuousNormal class

PriorCauchy-class

PriorCauchy Class

PriorHalfNormal-class

PriorHalfNormal Class

SimSampleSize-class

SimSampleSize Class

SimTreatmentList-class

SimTreatmentList Class

PriorExponential-class

PriorExponential Class

PriorNormal-class

PriorNormal Class

SimOutcomeList-class

SimOutcomeList Class

Treatment-class

Treatment Class

UniformPrior-class

UniformPrior Class

SimDataList-class

SimDataList Class

TimeToEvent-class

TimeToEvent class

SimBorrowingList-class

SimBorrowingList Class

PriorPoisson-class

PriorPoisson Class

baseline_covariates

Specify Correlated Baseline Covariates

PriorHalfCauchy-class

PriorHalfCauchy Class

Coerce a psborrow2 object to a data frame

Add Covariates for Model Adjustment

bernoulli_prior

Legacy function for the bernoulli prior

PriorBeta-class

PriorBeta Class

SimCovariateList-class

SimCovariateList Class

PriorBernoulli-class

PriorBernoulli Class

SimCovariates-class

SimCovariates Class

borrowing_hierarchical_commensurate

Hierarchical commensurate borrowing

check_data_matrix_has_columns

Check Data Matrix for Required Columns

check_fixed_external_data

Create a Fixed External Data Object

build_model_string

Build the model string by interpolating the Stan template

Combine objects in psborrow2

Legacy function for the beta prior

Binary Cut-Off Transformation

SimVarBin-class

SimVarBin class

Create binary covariate

Cut Off Functions

create_analysis_obj

Compile MCMC sampler using STAN and create analysis object

create_alpha_string

Create alpha string

custom_enrollment

Create a DataSimEnrollment Object

enrollment_constant

Constant Enrollment Rates

create_baseline_object

Create Baseline Data Simulation Object

eval_constraints

Evaluate constraints

SimVarCont-class

SimVarCont class

Legacy function for the cauchy prior

create_data_matrix

Create Data Matrix

create_simulation_obj

Compile MCMC sampler using STAN and create simulation object

possible_data_sim_vars

Get All Variable Names in Simulated Data Model Matrix

Get Simulated Data from SimDataList object

get_cmd_stan_models

Get CmdStanModel objects for MCMCSimulationResults

Legacy function for the poisson prior

generate,BaselineObject-method

Generate Data for a BaselineObject

outcome_surv_exponential

Exponential survival distribution

Sample from Stan model

Legacy function for the normal prior

Legacy function for the gamma prior

Example data matrix

create_tau_string

Create tau string

outcome_surv_pem

Piecewise exponential survival distribution

Prior gamma distribution

prior_half_cauchy

Prior half-cauchy distribution

half_cauchy_prior

Legacy function for the half-cauchy prior

Simulated Survival Data

Generate Data from Object

generate,DataSimObject-method

Generate Data for a DataSimObject

half_normal_prior

Legacy function for the normal half prior

load_and_interpolate_stan_model

Load and interpolate Stan model

Set Drop Out Distribution

Set Enrollment Rates for Internal and External Trials

Prior cauchy distribution

borrowing_details

Legacy function for specifying borrowing details

prior_exponential

Prior exponential distribution

Create continuous covariate

rename_draws_covariates

Rename Covariates in draws Object

Simulation-class

Simulation Class

Set Clinical Cut Off Rule

sim_covariates_summ

Summarize the number of continuous and binary covariates in a SimCovariates object created by sim_covariates()

sim_treatment_list

Input treatment details for a simulation study

outcome_bin_logistic

Bernoulli distribution with logit parametrization

outcome_cont_normal

Normal Outcome Distribution

Input generated data for a simulation study

logistic_bin_outcome

Legacy function for binary logistic regression

Prior poisson distribution

prior_half_normal

Prior half-normal distribution

get_prior_string_covariates

Get prior string for all covariates

Load a Stan psborrow2 template

Get Quantiles of Random Data

Specify covariates for simulation study

treatment_details

Specify Treatment Details

Plot Probability Density Function Values

covariance_matrix

Create Covariance Matrix

weib_ph_surv_dist

Legacy function for the Weibull proportional Hazards survival distribution

set_transformations,BaselineObject-method

Set Transformations in Baseline Objects

Plot Probability Mass Function Values

psborrow2-package

psborrow2: Bayesian Dynamic Borrowing Analysis and Simulation

set_transformations

Set transformations in BaselineObject objects

create_data_simulation

Data Simulation

sim_covariate_list

Input covariate adjustment details for a simulation study

create_event_dist

Specify a Time to Event Distribution

Prior normal distribution

variable_dictionary

Create Variable Dictionary

Prior uniform distribution

Trim columns from Data Matrix Based on Borrowing object type

Legacy function for the exponential survival distribution

Get results for MCMCSimulationResults objects

Get method for Stan model

exponential_prior

Legacy function for the exponential prior

outcome_surv_weibull_ph

Weibull survival distribution (proportional hazards formulation)

prior_bernoulli

Prior bernoulli distribution

Trim Rows from Data Matrix Based on Borrowing object type

Show guide for objects with guides

Plot Prior Objects

Prior beta distribution

sim_outcome_list

Input outcome details for a simulation study

sim_borrowing_list

Input borrowing details for a simulation study

Set simulation study parameters for sample size

Borrowing-class

Borrowing Class

BorrowingHierarchicalCommensurate-class

BorrowingHierarchicalCommensurate class

BaselineDataList-class

Baseline Data Frame List

BinaryOutcome-class

BinaryOutcome class

BaselineObject-class

BaselineObject class for data simulation

ContinuousOutcome-class

ContinuousOutcome class

BaselineDataFrame-class

Baseline Data Frame Object

BorrowingNone-class

BorrowingNone class

Analysis Class

BorrowingFull-class

BorrowingFull class

DataSimFixedExternalData-class

Fixed External Control Data Object

DataSimObject-class

Data Simulation Object Class

OutcomeBinaryLogistic-class

OutcomeBinaryLogistic class

DataSimEnrollment-class

Enrollment Object