The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

progme

Extended Progression Models for Repeated Measures.

Tools for progressive-disease clinical trials: nonlinear mixed-effects progression models, delayed treatment onset estimation via profile likelihood, joint longitudinal-survival models for informative dropout, competing risks, biomarker-informed adaptive dosing, and simulation-based power/sample-size calculation.

Install

# install.packages("remotes")
remotes::install_github("MukulBijalwan/progme")

Quick start

library(progme)

# Simulate a trial with a 6-month delayed treatment effect
sim <- simulate_progression_trial(n_control = 60, n_treatment = 60,
                                  effect_size = -0.5, delay = 6,
                                  times = seq(0, 24, by = 3))

# Estimate the delay by profile likelihood
fit <- pmrm_delayed(y ~ time * trt, data = sim,
                    delay_estimation = "profile",
                    delay_grid = seq(0, 18, by = 3))
print(fit)
plot(fit, type = "profile_likelihood")

# Simulation-based power
p <- power_pmrm(n_per_arm = 100, effect_size = -0.5, delay = 6, n_sims = 100)
p$power

Authors

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.