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Analyzing bivariate ordinal data with CUB margins

机译:使用CUB边距分析双变量序数数据

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Statistical modelling for ordinal data has received a considerable attention in the literature, and a consolidated theory relying on Generalized Linear Model approach has been developed. In this article, we present an innovative technique for modelling bivariate ordinal data. In particular, we consider the method introduced by Plackett for constructing a one-parameter bivariate distribution from given margins, and we apply it in order to represent correlated ordinal variables which individually follows a CUB model. This is a univariate mixture distribution defined by the convex Combination of a Uniform and a shifted Binomial distribution whose parameters may be related to rater's covariates. The article shows how the bivariate distribution can be defined and how its characterizing parameter, which describes the association between the component random variables, can be related to the subject's covariates. The proposed approach is applied to the study of two key drivers of extra virgin olive oil consumption in Italy. The technique allows a representation of the data whose meaning can be easily interpreted providing useful information for management support.
机译:序数数据的统计建模在文献中已受到相当多的关注,并且已经开发了基于广义线性模型方法的合并理论。在本文中,我们提出了一种用于建模双变量序数数据的创新技术。特别是,我们考虑了Plackett引入的根据给定边距构造一参数双变量分布的方法,并应用该方法来表示独立遵循CUB模型的相关序数变量。这是由均值的凸组合和移位的二项式分布定义的单变量混合分布,其参数可能与评估者的协变量有关。本文介绍了如何定义双变量分布以及如何将描述成分随机变量之间关联的特征参数与受试者的协变量相关联。拟议的方法适用于研究意大利特级初榨橄榄油消费的两个主要驱动因素。该技术允许对数据进行表示,其含义可以轻松解释,为管理支持提供有用的信息。

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