Negative variance components and intercept-slope correlations greater than one in magnitude: how do such ``non-regular random intercept and slope models arise, and what should be done when they do?
From MaRDI portal
Publication:6615928
DOI10.1002/SIM.10070zbMATH Open1546.62115MaRDI QIDQ6615928
Chris Frost, Katy E. Morgan, Helen Bridge
Publication date: 8 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
boundary problemsmixed modelsimproper solutionsrandom slopesnon-positive semidefinite covariance matricessingular fit
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Estimating negative variance components from Gaussian and non-Gaussian data: a mixed models approach
- The Problem of Negative Estimates of Variance Components
- The Effect of Drop-Out on the Efficiency of Longitudinal Experiments
- Negative variance components for non-negative hierarchical data with correlation, over-, and/or underdispersion
- A note on a hierarchical interpretation for negative variance components
- Multiple Imputation for Model Checking: Completed‐Data Plots with Missing and Latent Data
- The interpretation of negative components of variance
- Linear mixed models for longitudinal data
This page was built for publication: Negative variance components and intercept-slope correlations greater than one in magnitude: how do such ``non-regular random intercept and slope models arise, and what should be done when they do?
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6615928)
