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Behaviormetrika
Article . 1999 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Negative Binomial Factor Analysis

Authors: Ogasawara, Haruhiko;

Negative Binomial Factor Analysis

Abstract

A latent variable model for observed variables representing frequencies is proposed. The data type for the model is a subjects by variables two-way frequency table. The model has two groups of latent variables. The first group of latent variables represents the characteristics of subjects and corresponds to common factors in factor analysis. On the other hand, each of latent variables in the second group is related to one of the manifest variables and corresponds to a specific factor in factor analysis. The manifest variables in the model, when given the values of common latent variables, follow the negative binomial distributions. The latent variables in the first and second groups are integrated out of the model. The parameters in the model are estimated by the marginal maximum likelihood method, using a kind of the EM algorithm. The communality, specificity, and reliability for an observed variable are defined.

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Keywords

marginal maximum likelihood, frequency table, Poisson distribution, specific factor, negative binomial distribution, communality

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold