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Random effects model

Known as: Random-effect model, Variance components, Random effects estimator 
In statistics, a random effects model, also called a variance components model, is a kind of hierarchical linear model. It assumes that the data… Expand
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Papers overview

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Highly Cited
2008
Highly Cited
2008
This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items… Expand
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Highly Cited
2008
Highly Cited
2008
Psycholinguistic data are often analyzed with repeated-measures analyses of variance (ANOVA), but this paper argues that mixed… Expand
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Highly Cited
2005
Highly Cited
2005
Abstract Gauss–Hermite quadrature is often used to evaluate and maximize the likelihood for random component probit models… Expand
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Highly Cited
2004
Highly Cited
2004
A random effects model is proposed for the analysis of binary dyadic data that represent a social network or directed graph… Expand
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Highly Cited
2003
Highly Cited
2003
A mold, which can be advantageously used for foam molding articles, has a bottom box with a cover. Means, such as locating pins… Expand
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Highly Cited
2000
Highly Cited
2000
Research conclusions in the social sciences are increasingly based on meta-analysis, making questions of the accuracy of meta… Expand
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Highly Cited
1999
Highly Cited
1999
Standard item response theory (IRT) models fit to dichotomous examination responses ignore the fact that sets of items (testlets… Expand
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Highly Cited
1995
Highly Cited
1995
 
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Highly Cited
1987
Highly Cited
1987
-Repeatability is a useful tool for the population geneticist or genetical ecologist, but several papers have carried errors in… Expand
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Highly Cited
1972
Highly Cited
1972
The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with… Expand
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