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Everything about Random effects model
Statistical model
In econometrics, a random effects model, also called a variance components model, is a statistical model where the model effects are random variables. It is a kind of hierarchical linear model, which assumes that the data being analysed are drawn from a hierarchy of different populations whose differences relate to that hierarchy. A random effects model is a special case of a mixed model. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Random effects modelA 5-minute orientation
- Skim a recent paper: An introduction to the full random effects modelInfluential work since 2022
- Pick up a classic book: Generalized linear models with random effectsThe most-reprinted book on the subject
- Read the landmark paper: A random‐effects regression model for meta‐analysisCited 694 times
- Go sideways: Analysis of covarianceA closely related topic
- Go sideways: One-way analysis of varianceA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A random‐effects regression model for meta‐analysis
A Bayesian Random Effects Model for Testlets
A random effects model for effect sizes.
Proportional hazards model with random effects
The nonlinear mixed effects model with a smooth random effects density
Restructuring effects in the rain model for random deposition
A Random Effects Model for Binary Data
Bayesian Inference for the Spatial Random Effects Model
🆕 Influential since 2022
An introduction to the full random effects model
Fixed-effect Versus Random-effects Models for Meta-analyses: Random-effects Models
Examining effects of air pollution on photovoltaic systems via interpretable random forest model
Model misspecification in stepped wedge trials: Random effects for time or treatment
Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects
📚 Books worth reading
Generalized linear models with random effectsYoungjo Lee · 2006
Richly Parameterized Linear ModelsJames S. Hodges · 2013- 📕Exponential random graph models for social networksDean Lusher, Johan Koskinen · 2012
Simulation modeling using @RiskWayne L. Winston · 1996
Industrial Data Analytics for Diagnosis and PrognosisShiyu Zhou, Yong Chen · 2021
Statistical Modelling of Survival Data with Random EffectsIl Do Ha, Jong-Hyeon Jeong · 2018- 📕Applications of Linear and Nonlinear ModelsErik Grafarend, Joseph L. Awange · 2016
- 📕Asymptotic analysis of the one-way random effects modelsMahdi Alkhamisi · 2000
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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