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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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Review
2018
Review
2018
Deep domain adaption has emerged as a new learning technique to address the lack of massive amounts of labeled data. Compared to… Expand
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Review
2017
Review
2017
This research explores how expressed emotional arousal in a consumer review affects reader perceptions of its helpfulness… Expand
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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
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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
1993
Highly Cited
1993
For many years, stock market analysts have argued that value strategies outperform the market. These value strategies call for… 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
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Highly Cited
1936
Highly Cited
1936
Part I. Introduction: 1. The general theory 2. The postulates of the classical economics 3. The principle of effective demand… Expand
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