A Joint Model for Unbalanced Nested Repeated Measures with Informative Drop-Out Applied to Ambulatory Blood Pressure Monitoring Data

Enas M. Ghulam, Jane C. Khoury, Roman Jandarov, Raouf S. Amin, Eleni Rosalina Andrinopoulou, Rhonda D. Szczesniak*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

This study proposes a Bayesian joint model with extended random effects structure that incorporates nested repeated measures and provides simultaneous inference on treatment effects over time and drop-out patterns. The proposed model includes flexible splines to characterize the circadian variation inherent in blood pressure sequences, and we assess the effectiveness of an intervention to resolve pediatric obstructive sleep apnea. We demonstrate that the proposed model and its conventional two-stage counterpart provide similar estimates of nighttime blood pressure but estimates on the mean evolution of daytime blood pressure are discrepant. Our simulation studies tailored to the motivating data suggest reasonable estimation and coverage probabilities for both fixed and random effects. Computational challenges of model implementation are discussed.

Original languageEnglish
Article number4452158
JournalBioMed Research International
Volume2022
DOIs
Publication statusPublished - 25 Feb 2022

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Copyright © 2022 Enas M. Ghulam et al.

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