Binomial-Beta Hierarchical Models for Ecological Inference

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Binomial-Beta Hierarchical Models for Ecological Inference

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Title: Binomial-Beta Hierarchical Models for Ecological Inference
Author: King, Gary; Rosen, Ori; Tanner, Martin

Note: Order does not necessarily reflect citation order of authors.

Citation: King, Gary, Ori Rosen, and Martin Tanner. 1999. Binomial-beta hierarchical models for ecological inference. Sociological Methods and Research 28(1): 61-90.
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Abstract: he authors develop binomial-beta hierarchical models for ecological inference using insights from the literature on hierarchical models based on Markov chain Monte Carlo algorithms and King’s ecological inference model. The new approach reveals some features of the data that King’s approach does not, can be easily generalized to more complicated problems such as general R C tables, allows the data analyst to adjust for covariates, and provides a formal evaluation of the significance of the covariates. It may also be better suited to cases in which the observed aggregate cells are estimated from very few observations or have some forms of measurement error. This article also provides an example of a hierarchical model in which the statistical idea of “borrowing strength” is used not merely to increase the efficiency of the estimates but to enable the data analyst to obtain estimates.
Published Version: doi:10.1177/0049124199028001004
Other Sources: http://gking.harvard.edu/files/binom.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4125130

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  • FAS Scholarly Articles [7470]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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