Spectral parameterization for linear mixed models applied to confounding of fixed effects by random effects

DOI10.1016/j.jspi.2018.09.004zbMath1421.62090OpenAlexW2889945558WikidataQ129223000 ScholiaQ129223000MaRDI QIDQ2317269

Patrick M. Schnell, Maitreyee Bose

Publication date: 9 August 2019

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2018.09.004

zbMATH Keywords

Gaussian processesspectral decompositionlinear mixed modelsdiagnosticsconfoundingcollinearityconditional autoregressive modelsANOVA-like models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Linear regression; mixed models (62J05) Analysis of variance and covariance (ANOVA) (62J10)

Uses Software

• GMRFLib
• spectralGP

Cites Work

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• Eigenvector matrices of symmetric tridiagonals
• Identification of the variance components in the general two-variance linear model
• Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love
• Gaussian Markov Random Fields
• Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease‐Mapping Models