ORCID Profile
0000-0001-7288-7710
Current Organisation
Instituto Tecnológico Metropolitano
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Publisher: Frontiers Media SA
Date: 23-04-2019
Publisher: Oxford University Press (OUP)
Date: 18-02-2021
Abstract: The investigation of the characteristics and attributes that make a brand prominent for shoppers is known as salience research. This line of study concentrates on influencing buying behaviors via the manipulation of shopping environments and food products. Such promotional strategies successfully attract massive food sales and therefore have been associated with changes in dietary patterns and the epidemic expansion of non-communicable diseases, like obesity. Marketers have empirically proven that global buying patterns are influenced by their salience strategies and techniques. However, despite the significance of such methods, empirical salience investigations have rarely been extended beyond their primary business focus to the field of health promotion. Therefore, this study is presenting a way of transferring the salience knowledge to the health promotion field in order to track dietary choices and possibly gain information to identify buying and eating behaviors connected to obesity. The salience literature from various disciplines permits to hypothesize that consumers are more likely to have unhealthy diets when food-choices and conditions are saliently manipulated. A quasi-experimental method (combining salience measures with Bayesian analysis) was used to test this proposition. The results support the hypothesis and endorse the introduced research tool. As predicted, data reflect the latest national overweight and obesity statistics and suggest that habitual unhealthy diets are more likely when salience strategies link food products to taste, social and emotional attributes. These preliminary findings encourage further investigation to enhance the method as a possible epidemiological tool.
Publisher: Frontiers Media SA
Date: 15-05-2018
Publisher: MDPI AG
Date: 08-07-2020
DOI: 10.3390/SYM12071140
Abstract: Data from some research fields tend to exhibit a positive skew. For ex le, in experimental psychology, reaction times (RTs) are characterised as being positively skewed. However, it is not unlikely that RTs can take a normal or, even, a negative shape. While the Ex-Gaussian distribution is suitable to model positively skewed data, it cannot cope with negatively skewed data. This manuscript proposes a distribution that can deal with both negative and positive skews: the exponential-centred skew-normal (ECSN) distribution. The mathematical properties of the proposed distribution are reported, and it is featured in two non-synthetic datasets.
Publisher: MDPI AG
Date: 04-03-2021
DOI: 10.3390/STATS4010014
Abstract: Expert knowledge elicitation (EKE) aims at obtaining in idual representations of experts’ beliefs and render them in the form of probability distributions or functions. In many cases the elicited distributions differ and the challenge in Bayesian inference is then to find ways to reconcile discrepant elicited prior distributions. This paper proposes the parallel analysis of clusters of prior distributions through a hierarchical method for clustering distributions and that can be readily extended to functional data. The proposed method consists of (i) transforming the infinite-dimensional problem into a finite-dimensional one, (ii) using the Hellinger distance to compute the distances between curves and thus (iii) obtaining a hierarchical clustering structure. In a simulation study the proposed method was compared to k-means and agglomerative nesting algorithms and the results showed that the proposed method outperformed those algorithms. Finally, the proposed method is illustrated through an EKE experiment and other functional data sets.
No related grants have been discovered for Carlos Javier Barrera Causil.