Sample size calculation using Markov chains for a one-arm study of heroin administration routes

Sample size calculations for trials with time-to-event outcomes are usually based on the assumption that an event – prototypically death in survival analysis occurs only once per sample unit. However, events like changes disease status or switches between treatment modalities may repeat over time. In such outcomes, standard formulae derived from classical time models not applicable. Instead, modeling repeating transition must precede actual calculation. Markov chains obvious choice to model transitions. Accordingly, order determine a one-arm feasibility and acceptability study of new drug intake route, we administration routes by homogeneous finite-state, higher-order chain. Assumptions about its matrix translate into multinomial distributions preferred at given points From these distributions, required can then be calculated according study’s specific question. this manuscript, first introduce method case preferences, before briefly discuss how proposed also used power-based calculation multi-arm trials.