Confounding adjustment performance of ordinal analysis methods in stroke studies

Zonneveld, Thomas P.; Aigner, Annette; Algra, Ale; Nederkoorn, Paul J.; Grittner, Ulrike; Kruyt, Nyika D.; Siegerink, Bob

doi:10.1371/journal.pone.0231670

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Description Of Simulation Studies1

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2021

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“…We focus on the recovery of parameters of interest given a causal model. In all simulations, we evaluate the performance of the point and interval estimators of the e ect of three covariates X [38], as they pertain to generation of latent information Y ⇤ , which is turned into ve-to-nine ratings categories (depending on the model generating the data) by thresholding the generated latent distribution (Figure 2).…”

Section: Description Of Simulation Studiesmentioning

confidence: 99%

Bridge Category Models: Development of Bayesian Modelling Procedures to Account for Bridge Ordinal Ratings for Disease Staging

Levy

Bobak

Azizgolshani

et al. 2021

Preprint

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Disease grading and staging is accomplished through the assignment of an ordinal rating. Bridge ratings occur when a rater assigns two adjacent categories. Most statistical methodology necessitates the use of a single ordinal category. Consequently, bridge ratings often go unreported in clinical research studies. We propose three methodologies (Expanded, Mixture, and Collapsed) Bridge Category Models, to account for bridge ratings. We perform simulations to examine the impact of our approaches on detecting treatment effects, and comment on a real-world scenario of staging liver biopsies. Results indicate that if bridge ratings are not accounted for, disease staging models may exhibit significant bias and precision loss. All models worked well when they corresponded to the data generating mechanism.

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Section: Description Of Simulation Studiesmentioning

confidence: 99%