Package: progme 0.1.0

progme: Extended Progression Models for Repeated Measures

Extended progression models for repeated measures in progressive disease clinical trials. Provides nonlinear mixed-effects progression models (linear, plateau, Emax, exponential decay), delayed treatment onset estimation by profile likelihood, joint longitudinal-survival models for informative dropout, competing-risks extensions, biomarker-informed adaptive dosing rules, and simulation-based power and sample-size calculation. The progression-model view of treatment effects, in which effects are characterised on the underlying disease trajectory rather than as additive shifts on the outcome scale, follows Raket (2022) <doi:10.1002/sim.9581>. The nonlinear mixed-effects machinery is built on the 'nlme' implementation described by Pinheiro and Bates (2000, ISBN 978-0-387-98957-0), and the joint modelling of longitudinal and time-to-event data follows Rizopoulos (2012, ISBN 978-1-4398-7286-4).

Authors:Mukul Bijalwan [aut, cre], Gunjan Aggrwal [aut], Mukul Jain [aut]