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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.packages("remotes")
remotes::install_github("MukulBijalwan/progme")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$powerThese 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.