Two-Stage Multi-Sample Cluster Analysis as a General Approach to Discriminant Analysis

Eisenblätter, D; Bozdogan, Hamparsum

doi:10.1007/978-94-009-3977-6_6

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Information Complexity Criterion In Model Selection Process1

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2011

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Cited by 4 publications

(1 citation statement)

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“…Following Eisenblätter and Bozdogan (1987), Bozdogan and Sclove (1984) and Liberati et al (2009), it is easy to adapt such criterion to our clustering case:…”

Section: Information Complexity Criterion In Model Selection Processmentioning

confidence: 99%

An optimal cluster-based approach for Subgroup Analysis using Information Complexity Criterion

Attoma

Liberati

2011

IJBIDM

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Subgroup Analysis (SA) is a helpful technique in the context of randomised experiments and in observational studies. With reference to program evaluation, it helps in determining whether and how treatment effects vary across subgroups induced by baseline covariates. However, the choice of the optimal number of subgroups is often ambiguous and causes concern. Here, SA is conducted using the cluster-based approach introduced in D' Attoma and Camillo (2011) and the usage of the Information Complexity Criterion to select the optimal number of groups is proposed. A simulation study and a real case have been illustrated to show such promising approach.

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“…Following Eisenblätter and Bozdogan (1987), Bozdogan and Sclove (1984) and Liberati et al (2009), it is easy to adapt such criterion to our clustering case:…”

Section: Information Complexity Criterion In Model Selection Processmentioning

confidence: 99%

An optimal cluster-based approach for Subgroup Analysis using Information Complexity Criterion

Attoma

Liberati

2011

IJBIDM

View full text Add to dashboard Cite

show abstract

Information and Entropy in Cluster Analysis

Bock

1994

Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

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Aic-Replacements for Some Multivariate Tests of Homogeneity with Applications in Multisample Clustering and Variable Selection

Bozdogan

Sclove

Gupta

1994

Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

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Two-Stage Multi-Sample Cluster Analysis as a General Approach to Discriminant Analysis

Cited by 4 publications

References 15 publications

An optimal cluster-based approach for Subgroup Analysis using Information Complexity Criterion

An optimal cluster-based approach for Subgroup Analysis using Information Complexity Criterion

Information and Entropy in Cluster Analysis

Aic-Replacements for Some Multivariate Tests of Homogeneity with Applications in Multisample Clustering and Variable Selection

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