Demand for gambling: development and assessment of a gambling purchase task

Self-report purchase tasks are a novel approach examining the reinforcing value of addictive behaviour relative to increasing monetary costs required to access the addictive behaviour (i.e. demand). These measures reveal a positive relationship between the indices of demand and addiction problem severity and can elucidate factors associated with motivation for substance use. Gambling is an addictive behaviour that has not been examined using this paradigm. This study seeks to adapt and examine the purchase task for gambling behaviour. A gambling purchase task was devised that asked individuals how often per month they would gamble at various cover charges. Participants were 73 adults from the community with either gambling disorder (n = 28) or alcohol use disorder (n = 24) or were a healthy control (n = 21). Both the alcohol and gambling purchase tasks were administered. Results demonstrate discriminant validity of the gambling purchase task, as individuals with gambling disorder have significantly greater demand for accessing gambling than other groups. The alcohol purchase task also evidenced discriminant validity in that individuals with alcohol use disorder have significantly greater demand for alcohol than other groups. These findings support the use of the gambling purchase task to assess the demand for gambling.     

Stock investors’ preference for short-term vs. long-term bonuses

Bonuses in the finance sector may be based on too short time intervals for environmental and social factors to be taken into account in investment decisions. We report two experiments to investigate whether investors prefer short-term to long-term bonuses. In Experiment 1 employing 27 undergraduates, preferences were measured for four short-term certain bonuses, evenly distributed across a time interval, and one certain long-term bonus at the end of the time interval. A majority chose the short-term bonuses, and in order for the long-term bonus to be equally preferred it had to be about 40% higher than the four added short-term bonuses. Experiment 2 employing another 36 undergraduates introduced outcome uncertainty that more accurately reflects the choices stock investors face. The participants again choose between a long-term bonus and four distributed short-term bonuses. It was shown that uncertainty made more participants prefer the long-term bonus to the added short-term bonuses than when the outcome was certain. A smaller increase of the long-term bonus of about 20% was now required to make it equally attractive as the four added short-term bonuses.     

A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

Statistical Methods & Applications - In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The...     

Empirical Likelihood Inference for the Rao‐Hartley‐Cochran Sampling Design

The Hartley‐Rao‐Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley‐Rao‐Cochran sampling design. The approach proposed intrinsically incorporates sampling weights, auxiliary information and allows for large sampling fractions. It can be used to construct confidence intervals. In a simulation study, we show that the coverage may be better for the empirical likelihood confidence interval than for standard confidence intervals based on variance estimates. The approach proposed is simple to implement and less computer intensive than bootstrap. The confidence interval proposed does not rely on re‐sampling, linearization, variance estimation, design‐effects or joint inclusion probabilities.     

Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Development and validation of a Citizenship Attributional Style Questionnaire

Attribution theory remains popular in the social sciences and often informs education studies. However, attributional style questionnaires tend to reflect the context-dependent character of the theory and existing measures have been found to have poor psychometric properties. Clearly, both issues need to be carefully considered by researchers prior to them applying any scales that incorporate attributional dimensions. Here we report on the development of a reliable and valid measure that applies an attributional style within the context of citizenship. Two separate studies were conducted to inform the development of the Citizenship Attributional Style Questionnaire (CASQ). The factor loadings of eight positive and eight negative events for the internality and stability dimensions were found to range between .41 and .75. The Cronbach’s alpha reliability of positive and negative events were found to be .79 and .74, respectively. While CASQ is seen to be a reliable and valid measure, the results also indicate broader psychometric properties than many of the instruments currently used in studies with an attributional approach.     

On the Nearness of Records to Population Quantiles with Respect to Order Statistics in the Sense of Pitman Closeness

In this paper, Pitman closeness criterion is used to compare the nearness of record values and order statistics from two independent samples to a specific population quantile of the parent distribution while the underlying distributions are the same. General expressions for the associated Pitman closeness probability are obtained when the support of the parent distribution is bounded and also unbounded. Some distribution-free results are achieved for symmetric distributions. The exponential and uniform distributions are considered for illustrative proposes and exact expressions are obtained in each case.