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Marginal model

Known as: Marginal 
In statistics, marginal models (Heagerty & Zeger, 2000) are a technique for obtaining regression estimates in multilevel modeling, also called… Expand
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Papers overview

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Highly Cited
2011
Highly Cited
2011
Many researchers and journals place a strong emphasis on the sign and statistical significance of effects—but often there is very… Expand
Highly Cited
2004
Highly Cited
2004
Dans le cadre de sa propre theorie formelle de l'inference causale contrefactuelle, l'A. presente quelques methodes et outils… Expand
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Highly Cited
2003
Highly Cited
2003
The ‘sparse Bayesian’ modelling approach, as exemplified by the ‘relevance vector machine’, enables sparse classification and… Expand
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Highly Cited
2002
Highly Cited
2002
Human evaluations of machine translation are extensive but expensive. Human evaluations can take months to finish and involve… Expand
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Highly Cited
2000
Highly Cited
2000
Robins (1993, 1994, 1997, 1998ab) has developed a set of causal or counterfactual models, the structural nested models (SNMs… Expand
Highly Cited
1995
Highly Cited
1995
Abstract In the context of Bayes estimation via Gibbs sampling, with or without data augmentation, a simple approach is developed… Expand
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Highly Cited
1995
Highly Cited
1995
Abstract. The paper develops and analyzes a model of a firm's market value as it relates to contemporaneous and future earnings… Expand
Highly Cited
1993
Highly Cited
1993
For many years, stock market analysts have argued that value strategies outperform the market. These value strategies call for… Expand
Review
1990
Review
1990
Abstract Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three… Expand
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Highly Cited
1960
Highly Cited
1960
CONSIDER Table 1. It represents in its formal characteristics a situation which arises in the clinical-social-personality areas… Expand