Bayesian Estimation for the Exponentiated Weibull Model via Markov Chain Monte Carlo Simulation

Bayesian estimation for the two unknown parameters and the reliability function of the exponentiated Weibull model are obtained based on generalized order statistics. Markov chain Monte Carlo (MCMC) methods are considered to compute the Bayes estimates of the target parameters. Our computations are based on the balanced loss function which contains the symmetric and asymmetric loss functions as special cases. The results have been specialized to the progressively Type-II censored data and upper record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.     

The Emotional Experience and Expression of Anger: Children’s Perspectives

The purpose of this study was to explore and identify key themes related to a child’s experience of anger. The existing literature on children’s emotional experiences stems from adult perceptions and interpretations; this study was envisioned to investigate the experience of anger among children using their own words. Furthermore, this study was designed to illustrate a contextual perspective of children’s emotional knowledge, so that teachers, social workers, counsellors and other child mental health professionals may be able to relate and interpret children’s emotional experiences. Participants were male and female students, aged 8–9 years and in a regular grade three classroom within a community school. Through the use of semi-structured interview focus groups conducted over a span of 10 weeks, participants were invited to disclose their understandings of anger and how they experienced it. Results were analyzed via a content analysis that resulted in five themes. These themes consisted of understanding anger, origins of anger, consequences of anger, regulation and resolution of anger, and finally relations with others. Results and implications of the findings were discussed.     

Mixed probability models for dry and wet spells

When identifying the best model for representing the behavior of rainfall distribution based on a sequence of dry (wet) days, focus is usually given on the fitted model with the least number of estimated parameters. If the model with lesser number of parameters is found not adequate for describing a particular data distribution, the model with a higher number of parameters is recommended. Based on several probability models developed by previous researchers in this field, we propose five types of mixed probability models as the alternative to describe the distribution of dry (wet) spells for daily rainfall events. The mixed probability models comprise of the combination of log series distribution with three other types of models, which are Poisson distribution (MLPD), truncated Poisson distribution (MLTPD), and geometric distribution (MLGD). In addition, the combination of the two log series distributions (MLSD) and the mixed geometric with the truncated Poisson distribution (MGTPD) are also introduced as the alternative models. Daily rainfall data from 14 selected rainfall stations in Peninsular Malaysia for the periods of 1975 to 2004 were used in this present study. When selecting the best probability model to describe the observed distribution of dry (wet) spells, the Akaike’s Information Criterion (AIC) was considered. The results revealed that MLGD was the best probability model to represent the distribution of dry spells over the Peninsular.     

Preference reversals: Time and again

This paper sheds new light on the preference reversal phenomenon by analyzing decision times in the choice task. In a first experiment, we replicated the standard reversal pattern and found that choices associated with reversals take significantly longer than non-reversals, and non-reversal choices take longer whenever long-shot lotteries are selected. These results can be explained by a combination of noisy lottery evaluations (imprecise preferences) and an overpricing phenomenon associated with the compatibility hypothesis. The first cause explains the existence of reversals, while the second explains the predominance of a particular type thereof. A second experiment showed that the overpricing phenomenon can be shut down, greatly reducing reversals, by using ranking-based, ordinally-framed evaluation tasks. This experiment also disentangled the two determinants of reversals, because imprecise evaluations still deliver testable predictions on decision times even in the absence of the overpricing phenomenon. Strikingly, when unframed ranking tasks were used, decision times in the choice phase were greatly reduced, even though this phase was identical across treatments. This observation is consistent with psychological insights on conflicting decision processes.     

The arbitrariness and normativity of social conventions

This paper investigates a puzzling feature of social conventions: the fact that they are both arbitrary and normative. We examine how this tension is addressed in sociological accounts of conventional phenomena. Traditional approaches tend to generate either synchronic accounts that fail to consider the arbitrariness of conventions, or diachronic accounts that miss central aspects of their normativity. As a remedy, we propose a processual conception that considers conventions as both the outcome and material cause of much human activity. This conceptualization, which borrows from the économie des conventions as well as critical realism, provides a novel perspective on how conventions are nested and defined, and on how they are established, maintained and challenged.     

Estimation of parameters of the inverse gaussian-weibull mixture model

The main objective of this work is to estimate the 5-dime-nsional vector of parameters (p,μ,λ,α,c) of the mixture of an Inverse Gaussian IG(μ,λ) and Weibull W(α,c) distributions with mixing proportion p. We use the maximum Likelihood method (MLM) and the weighted maximum likelihood method (WMLM), both under the sampling schemes suggested by Hosmer (1973). Simulation study shows that the WMLM performs best, when Hosmer's model 2 is used, in the sense of minimizing the mean square error.     

Optimal designs for regional bridging studies using the Bayesian power prior method

As described in the ICH E5 guidelines, a bridging study is an additional study executed in a new geographical region or subpopulation to link or “build a bridge” from global clinical trial outcomes to the new region. The regulatory and scientific goals of a bridging study is to evaluate potential subpopulation differences while minimizing duplication of studies and meeting unmet medical needs expeditiously. Use of historical data (borrowing) from global studies is an attractive approach to meet these conflicting goals. Here, we propose a practical and relevant approach to guide the optimal borrowing rate (percent of subjects in earlier studies) and the number of subjects in the new regional bridging study. We address the limitations in global/regional exchangeability through use of a Bayesian power prior method and then optimize bridging study design with a return on investment viewpoint. The method is demonstrated using clinical data from global and Japanese trials in dapagliflozin for type 2 diabetes.     

Identity in old clothes: the socio-cultural dynamics of second-hand clothing in Irbid,Jordan

This paper investigates the socio-cultural dynamics underlying the consumption of second-hand clothing (al-Balih) in Irbid city, northern Jordan. It primarily examines the various images and meanings that consumers attach to used clothes imported primarily from the West. Al-Balih is conceived of as a social space where multiple imaginations and images meet and interact. Put another way, it tends to blur the conventional socio-economic distinctions that mark Jordanian society. In light of the recent economic hardship that Jordanians have faced due to the late alarming rise in most commodity prices, more people are turning to shopping at second-hand stores. The growth of the second-hand clothing trade can be seen as a testament to the strong demand by consumers for varied and inexpensive products. The paper adopts an anthropological framework in terms of its methodology and analysis. Ethnographic data were collected primarily through conducting in-depth interviews with consumers and shops owners.