Incorporating measurement error in the estimation of autoregressive models for longitudinal data

DOI10.1016/0378-3758(94)90186-4zbMath0804.62097OpenAlexW2036277738WikidataQ59745814 ScholiaQ59745814MaRDI QIDQ1338346

Christopher H. Schmid, Mark R. Segal, Bernard Rosner

Publication date: 18 December 1994

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)90186-4

zbMATH Keywords

confidence intervalslongitudinal datatime seriesmaximum likelihood estimatescoverage probabilityunderestimationmeasurement errorsimulation studyfirst-order autoregressive modelunbiasedbiasedordinary least squares estimatespulmonary function

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Estimation in Semiparametric Transition Measurement Error Models for Longitudinal Data, Modeling of Multivariate Monotone Disease Processes in the Presence of Misclassification, Fully Nonparametric Regression Modelling of Misclassified Censored Time-to-Event Data, Structural Inference in Transition Measurement Error Models for Longitudinal Data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Formulation and estimation of dynamic models using panel data
• Analysis of Repeated Measures
• PARAMETER ESTIMATION FOR LOW‐ORDER AUTO‐REGRESSIVE MODELS WITH MISSING VALUES
• Bayesian analysis of a three-component hierarchical design model