Mixed‐effects models for health care longitudinal data with an informative visiting process: A Monte Carlo simulation study

DOI10.1111/STAN.12188arXiv1808.00419OpenAlexW3100071030WikidataQ92365767 ScholiaQ92365767MaRDI QIDQ6067656

Unnamed Author, Alessandro M. Gasparini, Michael J. Sweeting, Unnamed Author, Michael J. Crowther, Jessica K. Barrett, Keith Abrams

Publication date: 14 December 2023

Published in: Statistica Neerlandica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1808.00419

zbMATH Keywords

longitudinal dataMonte Carlo simulationselection biasmixed-effects modelselectronic health recordsinformative visiting processinverse intensity of visiting weightingrecurrent-events models

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Statistics (62-XX) Applications of statistics (62Pxx)

Cites Work

• Cox's regression model for counting processes: A large sample study
• Longitudinal data with follow-up truncated by death: match the analysis method to research aims
• Joint Models for Longitudinal and Time-to-Event Data
• Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
• Longitudinal data analysis for generalized linear models with follow-up dependent on outcome-related variables
• Analysis of Longitudinal Data in the Presence of Informative Observational Times and a Dependent Terminal Event, with Application to Medical Cost Data
• Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
• Biased and unbiased estimation in longitudinal studies with informative visit processes

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