Multiple membership multiple classification (MMMC) models

By William J. Browne, Harvey Goldstein, J. Rasbash. 2001

396 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Genetics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3da06257c7f815aecb15b44cd178112beee1664e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. George Leckie
2. P. Angermeier
3. Eric Hallerman
4. J. Roberts
5. Andrew Bell
6. Kelvyn Jones
7. J. Rasbash
8. J. Jenkins

In Genetics

1. George Leckie
2. P. Angermeier
3. Eric Hallerman
4. J. Roberts
5. D. Oberwittler

In Statistics and Probability

1. George Leckie
2. Kelvyn Jones
3. P. Angermeier
4. Eric Hallerman
5. J. Roberts
6. Joris Knoben
7. Andrew Bell
8. R. Pillinger

Citations in the corpus

• The Effects of Neighbourhood Poverty on Adolescent Problem Behaviours: A Multi-level Analysis Differentiated by Gender and Ethnicity (2007, background): “The advance of more sophisticated statistical techniques as cross-classified multilevel analysis will hopefully render integrative approaches to ecological context effects easier to pursue (Browne et al., 2001).”
• Age, Period and Cohort Processes in Longitudinal and Life Course Analysis: A Multilevel Perspective (2015, background): “…data (that is survey data with multiple surveys over time) apparently suitable to be modelled with a multilevel cross-classified structure (Browne et al. 2001), whereby individuals are nested within cohort groups and periods of time, but periods are not nested within cohort groups or…”
• Distance, dams and drift: what structures populations of an endangered, benthic stream fish? (2013, methodology): “A Bayesian approach naturally accommodates this ‘multiple-membership model’ error structure and allows the proper estimation of the posterior mean and credible limits of effect sizes (Browne et al., 2001; Hadfield, 2010).”
• Multilevel Approaches and the Firm‐Agglomeration Ambiguity in Economic Growth Studies (2012, positive): “1995, Combes 2000, Rosenthal and Strange 2003, Brülhart and Mathys 2008). The literature argues that externalities or spillovers occur if an innovation or growth improvement implemented by a certain enterprise increases the performance of other enterprises without requiring the benefiting enterprise”
• The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement (2009, background): “The importance of schools that are attended in earlier phases of schooling has been reported before in the literature (Rasbash and Goldstein, 1994; Goldstein and Sammons, 1997; Browne et al., 2001; Goldstein et al., 2007).”
• Children's educational progress: partitioning family, school and area effects (2010, methodology): “to partition the response variation between pupils, schools and families while explicitly allowing for the non-hierarchical nature of the data (Browne et al., 2001; Fielding and Goldstein, 2006; Rasbash and Browne, 2001, 2008).”
• Is Textual Similarity Invariant under Machine Translation? Evidence Based on the Political Manifesto Corpus (2026, unknown): “…at hand (original language model pairs for the baseline, best-model, and performance-equivalence hypotheses; multilingual model pairs for the multilingual hypothesis), derived from a crossed multi-membership random-effects fit [12] that pools across all reference-class pairs in language L .”