A visualization method measuring the performance of biomarkers for guiding treatment decisions

Biomarkers that predict efficacy and safety for a given drug therapy become increasingly important for treatment strategy and drug evaluation in personalized medicine. Methodology for appropriately identifying and validating such biomarkers is critically needed, although it is very challenging to develop, especially in trials of terminal diseases with survival endpoints. The marker‐by‐treatment predictiveness curve serves this need by visualizing the treatment effect on survival as a function of biomarker for each treatment. In this article, we propose the weighted predictiveness curve (WPC). Based on the nature of the data, it generates predictiveness curves by utilizing either parametric or nonparametric approaches. Especially for nonparametric predictiveness curves, by incorporating local assessment techniques, it requires minimum model assumptions and provides great flexibility to visualize the marker‐by‐treatment relationship. WPC can be used to compare biomarkers and identify the one with the highest potential impact. Equally important, by simultaneously viewing several treatment‐specific predictiveness curves across the biomarker range, WPC can also guide the biomarker‐based treatment regimens. Simulations representing various scenarios are employed to evaluate the performance of WPC. Application on a well‐known liver cirrhosis trial sheds new light on the data and leads to discovery of novel patterns of treatment biomarker interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

A green space vision in Southeast Michigan’s most heavily industrialized area

Urban Ecosystems - In 2011, Marathon Petroleum Company LP, which has operated a refinery west of the Rouge River since 1959, initiated a voluntary property purchase program in the neighborhood...     

Multidimensional Resilience: Predictive and Construct Validity of the Individual,Family, and Community Resilience Profile

Few measures parallel the robust depth offered in the existing multidimensional and ecologically informed theories of resilience. This study sought to evaluate the test–retest reliability, construct, and predictive validity of the individual, family, and community resilience resource profile (IFCR-R). The IFCR-R measures a family’s access to resilience resources and protective factors across multiple ecological levels. Confirmatory factor analysis was used with a sample of n?=?810 low-income families. And 159 families completed multiple time point measures for test–retest reliability and predictive validity evaluation. Results of this study support the proposed multidimensional ecological structure of the IFCR-R and found that the IFCR-R offers an acceptable test–retest reliability and predictive validity for outcomes of mental and physical health.     

Unclaimed Prize Information Biases Perceptions of Winning in Scratch Card Gambling

Unclaimed prize information (i.e., the number of prizes still available to be won) is information commonly provided to scratch card gamblers. However, unless the number of tickets remaining to be purchased is also provided, this information is uninformative. Despite its lack of utility in assisting gamblers in choosing the most favourable type of scratch card to play, we hypothesized that unclaimed prize information would bias participants’ judgments within a scratch card gambling context. In Experiment 1 (N?=?201), we showed that participants are influenced by this information such that they felt more likely to win, were more excited to play, and preferred to hypothetically purchase more of the scratch card with the greatest number of unclaimed prizes. In Experiment 2 (N?=?201), we attempted to ameliorate this bias by providing participants with the number of tickets remaining to be purchased and equating the payback percentages of all three games. The bias, although attenuated, still persisted in these conditions. Finally, in Experiment 3 (N?=?200), we manipulated the hypothetical scratch cards such that games with the highest number of unclaimed prizes were the least favourable, and vice versa. As in Experiment 2, participants still favoured cards with greater numbers of unclaimed prizes. Possible mechanisms underlying this bias are discussed. In conclusion, across three experiments, we demonstrate that salient unclaimed prize information is capable of exerting a strong effect over judgments related to scratch card games.     

Increased Urge to Gamble Following Near-Miss Outcomes May Drive Purchasing Behaviour in Scratch Card Gambling

Previous research into scratch card gambling has highlighted the effects of these games on players’ arousal and affective states. Specifically, near-miss outcomes in scratch cards (uncovering 2 of 3 needed jackpot symbols) have been associated with high levels of physiological and subjective arousal and negative emotional evaluations, including increased frustration. We sought to extend this research by examining whether near-misses prompted increases in gambling urge, and the subsequent purchasing of additional scratch cards. Participants played two scratch cards with varying outcomes with half of the sample experiencing a near-miss for the jackpot prize, and the other half experiencing a regular loss. Players rated their urge to continue gambling after each game outcome, and following the initial playing phase, were then able to use their winnings to purchase additional cards. Our results indicated that near-misses increased the urge to gamble significantly more than regular losses, and urge to gamble in the near-miss group was significantly correlated with purchasing at least one additional card. Although some players in the loss group purchased another card, there was no correlation between urge to gamble and purchasing in this group. Additionally, participants in the near-miss group who purchased additional cards reported higher levels of urge than those who did not purchase more cards. This was not true for the loss group: participants who experienced solely losing outcomes reported similar levels of urge regardless of whether or not they purchased more scratch cards. Despite near-misses’ objective status as monetary losses, the increased urge that follows near-miss outcomes may translate into further scratch card gambling for a subset of individuals .     

Data for the Sustainable Development Goals: Metrics for Evaluating Civil Registration and Vital Statistics Systems Data Relevance and Production Capacity,Illustrations with Nigeria

Three issues impinging on the potential use of Civil Registration and Vital Statistics (CRVS) data for the Sustainable Development Goals (SDGs) are analysed in the paper. These include CRVS data relevance, content and data production capacity of CRVS systems. The paper adopts a ‘data type’ approach to relevance and capacity and proposes two metrics based on a graded qualitative evaluation (GQE) methodology. One is a data-relevance metric for evaluating the relevance of CRVS data types to the SDGs. The second is a National Statistical Systems (NSS) data type production capacity metric used for evaluating the data production capacity of CRVS systems. CRVS data instrument analysis and the CRVS data production capacity are exemplified with the Nigerian CRVS system. Relevance assessment results suggest that CRVS systems can provide data relevant to 25% of the SDGs. However the SDG data contribution of CRVS depends on the ‘data type’ capacity of National CRVS systems. As the capacity assessment shows, the Nigerian CRVS system has ‘nominal’ capacity to produce all CRVS data types (fertility, mortality, migration, nuptiality and socio-economic) and ‘active’ and ‘latent’ capacities to provide data for some 21 SDG targets. However, it currently lacks ‘effective’ capacity to produce any of the data types for the SDGs. The paper has implications for goal setting and prioritization in evolving strategies to enhance the development of CRVS/NSS systems’ data capacities, especially in developing countries.     

To stay or to go? Postretirement housing choices of single Baby Boomer women

Single women of the Baby Boomer generation are often financially disadvantaged in the retirement planning process due to their lower accumulated savings compared to male retirees. This disadvantage impacts significant consumption decisions such as postretirement housing choices. This study uses the theory of planned behavior to examine how certainty in intentions influences preparing and planning for postretirement housing. A typology of single Baby Boomer women is developed based on their financial, demographic, and psychological circumstances. Each segment likely requires different informational strategies and financial services to foster proactive planning for retirement. Significant implications exist for social policy and the financial services sector.