Prediction and inverse estimation in repeated-measures models

DOI10.1016/0378-3758(94)00127-HzbMath0832.62067OpenAlexW2047046842MaRDI QIDQ1901764

Erkki P. Liski, Tapio Nummi

Publication date: 9 November 1995

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)00127-h

zbMATH Keywords

predictionEM algorithmlongitudinal datamaximum likelihoodcovariance structuressemivariograminverse predictionpaper testingrepeated measures models

Mathematics Subject Classification ID

Linear inference, regression (62J99) Survival analysis and censored data (62N99)

Related Items (2)

Likelihood Methods for Controlled Calibration ⋮ Analysis of growth curve data by using cubic smoothing splines

Uses Software

• SAS/STAT

Cites Work

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• Random-Effects Models for Longitudinal Data
• Prediction of future observations in growth curve models. With discussion and a reply by the author
• Prediction in growth curve models using the EM algorithm
• Unbalanced Repeated-Measures Models with Structured Covariance Matrices
• Empirical Bayes Estimation of Individual Growth-Curve Parameters and Their Relationship to Covariates
• An Approach to the Analysis of Repeated Measurements
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• Statistical Calibration: A Review
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• Maximum Likelihood Computations with Repeated Measures: Application of the EM Algorithm
• Best Linear Unbiased Prediction in the Generalized Linear Regression Model

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