Experimental Investigation on the Elicitation of Subjective Distributions

Elicitation methods aim to build participants' distributions about a parameter of interest. In most elicitation studies this parameter is rarely known in advance and hinders an objective comparison between elicitation methods. In two experiments, participants were first presented with a fixed random sequence of images and numbers and subsequently their subjective distributions of percentages of one of those numbers was elicited. Importantly, the true percentage was set in advance. The first experiment tested whether receiving instructions as to the elicitation method would assist in estimating a true value more accurately than receiving no instructions and whether accuracy was determined by the numerical skills of the participants. The second experiment sought to compare the elicitation method used in the first experiment with a variation of a graphical elicitation method. The results indicate that (i) receiving instructions as to the elicitation method does assist in producing estimates closer to a true percentage value, (ii) the level of numerical skills does not play a part in the accuracy of the estimation (Experiment 1), and (iii) although the average estimates of the betting and graphical method are not significantly different, the betting method leads to more precise estimations than the graphical method (Experiment 2). Both studies featured statistical procedures (functional data analysis and a novel clustering technique) not considered in past research on the elicitation of subjective distributions. The implications of these results are discussed in relation to a recent key study

Estimación por intervalos de probabilidad a posteriori para la proporción de estudiantes universitarios desertores

En este artículo se presenta la estimación por intervalos de probabilidad a posteriori de la proporción de estudiantes que desertan del Instituto Tecnológico Metropolitano (ITM) según algunos factores influyentes. Nuestro interés es determinar la proporción de estudiantes que desertan de dicha institución según los factores académico, laboral y personal. Se usó metodología bayesiana, implementando procesos de elicitación y método Delphi. Dentro de los resultados, se evidenció que, con una probabilidad del 95% se afirma que el factor laboral tiene un porcentaje a posteriori de incidencia en la deserción del ITM entre el 30,4% y 44,6%. Además, se notó que el factor laboral y el académico son los más influyentes en la deserción de la institución.This paper presents the estimation by posterior probability intervals of the proportion of students who drop out of Instituto Tecnológico Metropolitano (ITM) considering some influential factors. Our interest is to determine the proportion of students who drop out of the institution by academic factor, occupational and personal factor. To implement the Bayesian methodology we use the elicitation technique and the Delphi method. Within the results, showed that, with a probability of 95% we can say that the occupational factor have a posterior percentage of incidence on drop out of ITM between 30,4% and 44,6%. Also, notice that the occupational factor and the academic factor are the most influential in the drop out of the institution

Manipulating the alpha level cannot cure significance testing

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, and implications for applications. To boil all this down to a binary decision based on a p-value threshold of 0.05, 0.01, 0.005, or anything else, is not acceptable

Power Families of Bivariate Proportional Hazard Models

In this paper, we propose a general class of bivariate proportional hazard distributions, which is based on the family of asymmetric proportional hazard distributions and the bivariate Pareto copula. Distributional properties of the bivariate proportional hazard distribution are derived. We specialize the bivariate proportional hazard family of distributions to the normal case, and so we introduce the bivariate proportional hazard normal distribution. Parameter estimation by the maximum likelihood method of the bivariate proportional hazard normal distribution is then discussed. Finally, an application of the new bivariate distribution to real data is considered for illustrative purposes

Estimación por intervalos de probabilidad a posteriori para la proporción de estudiantes universitarios desertores

This paper presents the estimation by posterior probability intervals of the proportion of students who drop out of Instituto Tecnológico Metropolitano (ITM) considering some influential factors. Our interest is to determine the proportion of students who drop out of the institution by academic factor, occupational and personal factor. To implement the Bayesian methodology we use the elicitation technique and the Delphi method. Within the results, showed that, with a probability of 95% we can say that the occupational factor have a posterior percentage of incidence on drop out of ITM between 30,4% and 44,6%. Also, notice that the occupational factor and the academic factor are the most influential in the drop out of the institution.En este artículo se presenta la estimación por intervalos de probabilidad a posteriori de la proporción de estudiantes que desertan del Instituto Tecnológico Metropolitano (ITM) según algunos factores influyentes. Nuestro interés es determinar la proporción de estudiantes que desertan de dicha institución según los factores académico, laboral y personal. Se usó metodología bayesiana, implementando procesos de elicitación y método Delphi. Dentro de los resultados, se evidenció que, con una probabilidad del 95% se afirma que el factor laboral tiene un porcentaje a posteriori de incidencia en la deserción del ITM entre el 30,4% y 44,6%. Además, se notó que el factor laboral y el académico son los más influyentes en la deserción de la institución

Modulatory Effect of Chlorogenic Acid and Coffee Extracts on Wnt/β-Catenin Pathway in Colorectal Cancer Cells

The Wnt/β-Catenin pathway alterations present in colorectal cancer (CRC) are of special interest in the development of new therapeutic strategies to impact carcinogenesis and the progression of CRC. In this context, different polyphenols present in natural products have been reported to have modulatory effects against the Wnt pathway in CRC. In this study, we evaluate the effect of two polyphenol-rich coffee extracts and chlorogenic acid (CGA) against SW480 and HT-29 CRC cells. This involved the use of MTT and SRB techniques for cell viability; wound healing and invasion assay for the evaluation of the migration and invasion process; T cell factor (TCF) reporter plasmid for the evaluation of transciption factor (TCF) transcriptional activity; polymerase chain reaction (PCR) of target genes and confocal fluorescence microscopy for β-Catenin and E-Cadherin protein fluorescence levels; and subcellular localization. Our results showed a potential modulatory effect of the Wnt pathway on CRC cells, and we observed a reduction in the transcriptional activity of β-catenin. All the results were prominent in SW480 cells, where the Wnt pathway deregulation has more relevance and implies a constitutive activation of the signaling pathway. These results establish a starting point for the discovery of a mechanism of action associated with these effects and corroborate the anticancer potential of polyphenols present in coffee, which could be explored as chemopreventive molecules or as adjunctive therapy in CRC

Manipulating the Alpha Level Cannot Cure Significance Testing

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, and implications for applications. To boil all this down to a binary decision based on a p-value threshold of 0.05, 0.01, 0.005, or anything else, is not acceptable