Modelling dependency in multivariate paired comparisons: A log-linear approach [An article from: Mathematical Social Sciences]
Book Details
PublisherElsevier
ISBN / ASINB000PAU762
ISBN-13978B000PAU767
AvailabilityAvailable for download now
Sales Rank10,624,276
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Mathematical Social Sciences, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
A log-linear representation of the Bradley-Terry model is presented for multivariate paired comparison data, where judges are asked to compare pairs of objects on more than one attribute. By converting such data to multiple binomial responses, dependencies between the decisions of the judges as well as possible association structures between the attributes can be incorporated in the model, providing an advantage over parallel univariate analyses of individual attributes. The approach outlined gives parameters which can be interpreted as (conditional) log-odds and log-odds ratios. As the model is a generalised linear model, parameter estimation can use standard software and the GLM framework can be used to test hypotheses on these parameters.
Description:
A log-linear representation of the Bradley-Terry model is presented for multivariate paired comparison data, where judges are asked to compare pairs of objects on more than one attribute. By converting such data to multiple binomial responses, dependencies between the decisions of the judges as well as possible association structures between the attributes can be incorporated in the model, providing an advantage over parallel univariate analyses of individual attributes. The approach outlined gives parameters which can be interpreted as (conditional) log-odds and log-odds ratios. As the model is a generalised linear model, parameter estimation can use standard software and the GLM framework can be used to test hypotheses on these parameters.
