Robust estimation of occupation probabilities for coarsened multistate processes

Niklas Nyboe Maltzahn; Gergely Dániel Lukáts; Kjetil Røysland

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arXiv · 2606.27952

Robust estimation of occupation probabilities for coarsened multistate processes

Niklas Nyboe Maltzahn·Gergely Dániel Lukáts·Kjetil Røysland

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Abstract

We derive augmented inverse probability weighted estimators for occupation probabilities of multistate models under two levels of coarsening; right-censoring and baseline exposure. The key exchangeability assumption for identification is coarsening at random, while allowing for time-varying confounders, but not requiring Markov properties. Using existing techniques from causal inference and missing data literature, the derived estimators have highly desirable robustness and efficiency properties. These properties are demonstrated through both theoretical results, and a simulation study.

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Niklas Nyboe Maltzahn, Gergely Dániel Lukáts, Kjetil Røysland. 2026-06-26. Robust estimation of occupation probabilities for coarsened multistate processes. https://arxiv.org/abs/2606.27952

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