ArticleCommunications in statistics: Simulation and computation2017
Assessing type I error and power of multistate Markov models for panel data-A simulation study.
Article in Communications in statistics: Simulation and computation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Multistate Modeling of Clinical Trajectories and Outcomes in the ICU: A Proof-of-Concept Evaluation of Acute Kidney Injury Among Critically Ill Patients With COVID-19.Critical care explorations · 2022Article
- Duration of Carbapenemase-Producing Enterobacteriaceae Carriage in Hospital Patients.Emerging infectious diseases · 2020Article
- Treatment effect on ordinal functional outcome using piecewise multistate Markov model with unobservable baseline: an application to the modified Rankin scale.Journal of biopharmaceutical statistics · 2019Article
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Authors and funding
6 authors.
Funding
Abstract
Ordinal outcomes collected at multiple follow-up visits are common in clinical trials. Sometimes, one visit is chosen for the primary analysis and the scale is dichotomized amounting to loss of information. Multistate Markov models describe how a process moves between states over time. Here, simulation studies are performed to investigate the type I error and power characteristics of multistate Markov models for panel data with limited non-adjacent state transitions. The results suggest that the multistate Markov models preserve the type I error and adequate power is achieved with modest sample sizes for panel data with limited non-adjacent state transitions.
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