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Patient-physician communication has the potential to improve outcomes and satisfaction through the shared decision-making process (SDM). This study aims to assess the relationship between perception of SDM and demographic, clinical, and patient-reported outcomes in patients undergoing Hallux Valgus (HV) correction. A prospective analysis of 306 patients scheduled for HV surgery was completed. The CollaboRATE score was used to measure SDM. Multivariable linear regression model was used to assess whether SDM scores were associated with preoperative characteristics or postoperative outcome scores. The mean CollaboRATE score was 2.9 (SD 0.9) and did not differ by age, socioeconomic status, or sex. Lower CollaboRATE scores were associated with more symptoms of depression, lower socioeconomic status, and lower general health scores (p-value < 0.05). There was no association between SDM scores and postoperative outcome scores. In this study, patients with depressive symptoms and lower socioeconomic status had worse perceptions of SDM. There was no difference in postoperative outcomes among participants based on SDM scores. Level of Evidence: Level III, prospective observational study [ABSTRACT FROM AUTHOR]

Background: To demonstrate bioequivalence between two drug formulations, a pilot trial is often conducted prior to a pivotal trial to assess feasibility and gain preliminary information about the treatment effect. Due to the limited sample size, it is not recommended to perform significance tests at the conventional 5% level using pilot data to determine if a pivotal trial should take place. Whilst some authors suggest to relax the significance level, a Bayesian framework provides an alternative for informing the decision-making. Moreover, a Bayesian approach also readily permits possible incorporation of pilot data in priors for the parameters that underpin the pivotal trial. Methods: We consider two-sequence, two-period crossover designs that compare test (T) and reference (R) treatments. We propose a robust Bayesian hierarchical model, embedded with a scaling factor, to elicit a Go/No-Go decision using predictive probabilities. Following a Go decision, the final analysis to formally establish bioequivalence can leverage both the pilot and pivotal trial data jointly. A simulation study is performed to evaluate trial operating characteristics. Results: Compared with conventional procedures, our proposed method improves the decision-making to correctly allocate a Go decision in scenarios of bioequivalence. By choosing an appropriate threshold, the probability of correctly (incorrectly) making a No-Go (Go) decision can be ensured at a desired target level. Using both pilot and pivotal trial data in the final analysis can result in a higher chance of declaring bioequivalence. The false positive rate can be maintained in situations when T and R are not bioequivalent. Conclusions: The proposed methodology is novel and effective in different stages of bioequivalence assessment. It can greatly enhance the decision-making process in bioequivalence trials, particularly in situations with a small sample size. [ABSTRACT FROM AUTHOR]

Aim: To translate and culturally adapt the FRAIL scale into Spanish and perform a preliminary test of diagnostic accuracy in patients admitted to intensive care units. Design: Cross‐sectional diagnostic study. Methods: Five intensive care units (ICU) in Spain were participated. Stage 1: Three native Spanish‐speaking bilingual translators familiar with the field of critical care translated the scale from English into Spanish. Stage 2: Three native English‐speaking bilingual translators familiar with critical care medicine. Stage 3: Authors of the original scale compared the English original and back‐translated versions of the scale. Stage 4: Five nurses with more than 5 years of ICU experience and five critical care physicians assessed the comprehension and relevance of each of the items of the Spanish version in 30 patients of 3 different age ranges (<50, 50–65 and >65 years). Results: The FRAIL scale was translated and adapted cross‐culturally for patients admitted to intensive care units in Spain. The process consisted of four stages: translation, back translation, comparison and pilot test. There was good correspondence between the original scale and the Spanish version in 100% of the items. The participating patients assessed the relevance (content validity) and comprehensibility (face validity) of each of the items of the first Spanish version. The relevance of some of the items scored low when the scale was used in patients younger than 65 years. Conclusions: We have cross‐culturally adapted the FRAIL scale, originally in English, to Spanish for its use in the critical care medical setting in Spanish‐speaking countries. Implications for Professionals: Physicians and nurses can apply the new scale to all patients admitted to the intensive care units. Nursing care can be adapted according to frailty, trying to reduce the side effects of admission to these units for the most fragile patients. Reporting Method: The manuscript's authors have adhered to the EQUATOR guidelines, using the COSMIN reporting guideline for studies on the measurement properties of patient‐reported outcome measures. Patient or Public Contribution: In a pilot clinical study, we applied the first version of the FRAIL‐Spain scale to intensive care unit (ICU) patients. Five nurses with more than 5 years of ICU experience and five critical care physicians assessed the relevance (content validity) and comprehensibility (face validity) of the five items of the first Spanish version. Relevance was assessed using a 4‐point Likert scale ranging from 1 (no relevance) to 4 (high relevance), and comprehensibility was assessed as poor, acceptable or good. Each health professional applied the scale to three patients (total number of patients = 30) of three different age ranges (<50, 50–65 and >65 years) and recorded the time of application of the scale to each patient. Although the frailty scales were initially created by geriatricians to be applied to the elders, there is little experience with their application in critically ill patients of any age. Therefore, more information is needed to determine the relevance of using this scale in critical care patients. In this pilot study, we considered that nurses and critical care physicians should evaluate frailty using this adapted scale in adult patients admitted to the Intensive Care Units. [ABSTRACT FROM AUTHOR]

Since capital may not be abundant for banks, banks have to assess the efficiency of small and medium enterprises (SMEs) to efficiently and profitably allocate available funds. This study aims to generate criteria priority series for the decision process of commercial credit applications (DPCCAs) to conduct statistical hypothesis testing and produce information for researchers, decision-makers/managers. Having lots of criteria in assessing SME performance, analytic hierarchy process (AHP) — a multi-criteria decision-making method — is applied according to experts' views. By determining SMEs' indicator-criteria priorities, this study's priorities give information on SME growth potential, managerial competence and institutionalization which are rarely used in SMEs' credit evaluation in academic studies. This study also evaluates tolerated consistency boundary approach (TCBA) defined in Pekkaya's studies and generates priority-series that allows for statistical testing. The findings reveal that "profitability and business volume" with its sub-criteria of "operating profitability" have the highest priority, and then "stability and intelligence" with "repayment practices of debts" and "total income and stability in profitability" have quite high priorities among seven main- and 26 sub-criteria. This study contains some criteria which are not previously observed in the related literature, incorporates considerably more expert views, and shows to conduct statistical hypothesis tests by using the generated priority series via AHP for each criterion. [ABSTRACT FROM AUTHOR]

How should political decisions be made to ensure a high level of legitimacy in the eyes of ordinary citizens? In order to answer this question, we conducted six focus groups (N = 29) with adults (20-78 years old). We analyzed data using a thematic analysis, within the essentialist/realist framework and focused on the explicit meanings of the data. Two specific issues were explored: the adoption of the Euro and acceptance of Syrian orphan refugees. The bottom-up analysis revealed that participants considered two strategies of political decision-making (direct vote and representation based) and discussed the pros and cons of each process in detail. The results point out the importance of public deliberation, transparency, and the source of decision-making in evaluating the overall legitimacy of decisions-making process. Further, unlike popular belief that citizens are thirsty for direct democracy our results suggest that people are rather hesitant about placing big decisions into the hands of ordinary citizens, nor do they want to be burdened with making decisions about issues that might not affect them directly. Rather, people described representation-based decisions as legitimate if condition of transparency, deliberation, and trust in politicians is met. [ABSTRACT FROM AUTHOR]

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Purpose: To examine the impact of in situ simulation (ISS) with scripting on nursing staff's knowledge and confidence to initiate rapid response teams (RRTs) immediately after identifying patient condition deterioration. Background/Significance: Failure to rescue (FTR) related to delays in activation of RRT is on the rise, leading to poor patient outcomes. Lack of confidence, knowledge, and empowerment are associated with delayed activation of RRTs. As such, the nursing staff's confidence is integral in activating RRTs and FTR prevention. In situ simulation may help nurses increase their confidence, thus empowering timely RRT initiation. Methods: This quantitative pretest-posttest study used a convenience sample of nurses and nursing assistants. First, participants completed the Rapid Response Team Survey (RRTS) pretest. Then, they participated in the ISS scenario. Lastly, they completed debriefing and the RRTS posttest. Results: Pearson's correlation results showed no significant relationships between the variables. Dependent t-test results showed statistically significant increases between the pretest and posttest means (Part l, t = -5.51, p < .001, MD = 1.32; Part 2, t = -1.04, p < .01, MD = 3.1). These results suggest that ISS with scripting increased participants' knowledge and confidence in early activation of RRTs. Additionally, staff reported feeling more confident and empowered regarding future RRT decision-making and communication with other healthcare colleagues. Discussion: Early activation of RRTs prevents FTR. The results of this study suggest ISS with scripting increases staff's knowledge, confidence, and empowerment to activate RRTs. We recommend that hospital organizations adopt ISS with scripting to empower nurses to activate RRTs to prevent FTR. [ABSTRACT FROM AUTHOR]

We investigate what fraction of all significant results in website A/B testing is actually null effects (i.e., the false discovery rate (FDR)). Our data consist of 4,964 effects from 2,766 experiments conducted on a commercial A/B testing platform. Using three different methods, we find that the FDR ranges between 28% and 37% for tests conducted at 10% significance and between 18% and 25% for tests at 5% significance (two sided). These high FDRs stem mostly from the high fraction of true null effects, about 70%, rather than from low power. Using our estimates, we also assess the potential of various A/B test designs to reduce the FDR. The two main implications are that decision makers should expect one in five interventions achieving significance at 5% confidence to be ineffective when deployed in the field and that analysts should consider using two-stage designs with multiple variations rather than basic A/B tests. This paper was accepted by Eric Anderson, marketing. [ABSTRACT FROM AUTHOR]

A fuzzy set extension known as the hesitant fuzzy set (HFS) has increased in popularity for decision making in recent years, especially when experts have had trouble evaluating several alternatives by employing a single value for assessment when working in a fuzzy environment. However, it has a significant problem in its uses, i.e., considerable data loss. The probabilistic hesitant fuzzy set (PHFS) has been proposed to improve the HFS. It provides probability values to the HFS and has the ability to retain more information than the HFS. Previously, fuzzy regression models such as the fuzzy linear regression model (FLRM) and hesitant fuzzy linear regression model were used for decision making; however, these models do not provide information about the distribution. To address this issue, we proposed a probabilistic hesitant fuzzy linear regression model (PHFLRM) that incorporates distribution information to account for multi-criteria decision-making (MCDM) problems. The PHFLRM observes the input–output (IPOP) variables as probabilistic hesitant fuzzy elements (PHFEs) and uses a linear programming model (LPM) to estimate the parameters. A case study is used to illustrate the proposed methodology. Additionally, an MCDM technique called the technique for order preference by similarity to ideal solution (TOPSIS) is employed to compare the PHFLRM findings with those obtained using TOPSIS. Lastly, Spearman's rank correlation test assesses the statistical significance of two rankings sets. [ABSTRACT FROM AUTHOR]

In this paper, Kruskal-Wallis test is extended to deal with neutrosophic data in single valued form using score, accuracy and certainty functions to calculate ranks of SVNNs, also Mann-Whitney test is extended to deal with same data type which makes it possible to do a post-hoc test after rejecting null hypothesis using Neutrosophic Statistics Kruskal-Wallis test. Numerical examples were successfully solved showing the power of this new idea to deal with SVNNs and make statistical decisions on them. [ABSTRACT FROM AUTHOR]

Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this article, we extend the key ideas to disease areas outside of oncology, developing a robust Bayesian methodology for randomized, placebo-controlled basket trials with a continuous endpoint to enable borrowing of information across subtrials with similar treatment effects. After adjusting for covariates, information from a complementary subtrial can be represented into a commensurate prior for the parameter that underpins the subtrial under consideration. We propose using distributional discrepancy to characterize the commensurability between subtrials for appropriate borrowing of information through a spike-and-slab prior, which is placed on the prior precision factor. When the basket trial has at least three subtrials, commensurate priors for point-to-point borrowing are combined into a marginal predictive prior, according to the weights transformed from the pairwise discrepancy measures. In this way, only information from subtrial(s) with the most commensurate treatment effect is leveraged. The marginal predictive prior is updated to a robust posterior by the contemporary subtrial data to inform decision making. Operating characteristics of the proposed methodology are evaluated through simulations motivated by a real basket trial in chronic diseases. The proposed methodology has advantages compared to other selected Bayesian analysis models, for (i) identifying the most commensurate source of information and (ii) gauging the degree of borrowing from specific subtrials. Numerical results also suggest that our methodology can improve the precision of estimates and, potentially, the statistical power for hypothesis testing. [ABSTRACT FROM AUTHOR]

Introduction: In our research, we investigated the components, executive functions, and cognitive abilities underlying decision-making in sports performance using a computer-based test system. To define the athlete experience, we classified athletes according to an exact, unambiguous definition following international terminology, based on their performance, achievement, playing age, and sport's popularity. We hypothesize that team athlete with significant athletic experience will perform better on the executive function test. Methods: A cross-sectional study was conducted on team athletes N=52. The VTS-DT test was used to measure executive function. The classification of athlete experience was based on an internationally accepted taxonomy defined with scientific precision (SWANNN, 2015). Results: When classified by athlete experience, the athletes we studied fell into amateur and elite categories. The DT/S2 scores of the two groups were compared based on each factor. We obtained trend-like correlations for the factors 'number of reactions', 'number of stimulations,' and 'number of good responses. Correlation analysis was performed between the factors on a group-by-group basis. When examining the relationship between reaction time, we found that there is a strong relationship with the number of stimulations (amateurs: r = -0.80; elite athletes: r = -0.87) since the faster someone is (i.e., the less reaction time), the more times they can respond to stimulations. Looking at the results for elite athletes, we also observe a moderately strong relationship between reaction time and the number of good responses (r = -0.68). We may suggest that experienced athletes could produce better responses faster than less professional athletes. Conclusions: Our hypotheses were partially confirmed, as we found a trend-like correlation that elite athletes scored higher on the DT test, which examined athletes' executive functions in a complex, adaptive way. Our research demonstrates that, on the one hand, it is worthwhile for coaches to build on experienced athletes when assembling a team, in addition to the momentum of young athletes, and that the development of executive functions and cognitive skills can improve the performance of athletes. [ABSTRACT FROM AUTHOR]

Introduction/Objectives: Due to the risks associated with sedative hypnotic medications in older adults, our study evaluated the impact of a multidisciplinary approach to deprescribing in geriatric primary care clinics. Methods: The study was a retrospective review of older adults at 2 academic, geriatric primary care clinics who were prescribed sedativehypnotic medications. Patients were mailed an education packet of information that included working with the clinical pharmacy team, behavioral health team, or both in order to deprescribe their sedative-hypnotic medication. The study assessed the rate of discontinuation of sedative-hypnotic medications between the different intervention groups. Results: The study included 93 older adults with a mean age of 81.3 years and 39.8% discontinuation rate of their medication. The number of falls decreased in patients who discontinued use compared to when previously using a sedative hypnotic medication. Conclusion: Patients are more likely to discontinue their sedative hypnotic medication with a multidisciplinary approach, specifically with primary care provider support. [ABSTRACT FROM AUTHOR]

Biomedical research has come to rely on p-values as a deterministic measure for data-driven decision-making. In the largely extended null hypothesis significance testing for identifying statistically significant differences among groups of observations, a single p-value is computed from sample data. Then, it is routinely compared with a threshold, commonly set to 0.05, to assess the evidence against the hypothesis of having non-significant differences among groups, or the null hypothesis. Because the estimated p-value tends to decrease when the sample size is increased, applying this methodology to datasets with large sample sizes results in the rejection of the null hypothesis, making it not meaningful in this specific situation. We propose a new approach to detect differences based on the dependence of the p-value on the sample size. We introduce new descriptive parameters that overcome the effect of the size in the p-value interpretation in the framework of datasets with large sample sizes, reducing the uncertainty in the decision about the existence of biological differences between the compared experiments. The methodology enables the graphical and quantitative characterization of the differences between the compared experiments guiding the researchers in the decision process. An in-depth study of the methodology is carried out on simulated and experimental data. Code availability at https://github.com/BIIG-UC3M/pMoSS. [ABSTRACT FROM AUTHOR]

If artificial intelligence (AI) is to help solve individual, societal and global problems, humans should neither underestimate nor overestimate its trustworthiness. Situated in-between these two extremes is an ideal 'Goldilocks' zone of credibility. But what will keep trust in this zone? We hypothesise that this role ultimately falls to the social cognition mechanisms which adaptively regulate conformity between humans. This novel hypothesis predicts that human-like functional biases in conformity should occur during interactions with AI. We examined multiple tests of this prediction using a collaborative remembering paradigm, where participants viewed household scenes for 30 s vs. 2 min, then saw 2-alternative forced-choice decisions about scene content originating either from AI- or human-sources. We manipulated the credibility of different sources (Experiment 1) and, from a single source, the estimated-likelihood (Experiment 2) and objective accuracy (Experiment 3) of specific decisions. As predicted, each manipulation produced functional biases for AI-sources mirroring those found for human-sources. Participants conformed more to higher credibility sources, and higher-likelihood or more objectively accurate decisions, becoming increasingly sensitive to source accuracy when their own capability was reduced. These findings support the hypothesised role of social cognition in regulating AI's influence, raising important implications and new directions for research on human–AI interaction. [ABSTRACT FROM AUTHOR]

The discussion on the use and misuse of p-values in 2016 by the American Statistician Association was a timely assertion that statistical concept should be properly used in science. Some researchers, especially the economists, who adopt significance testing and p-values to report their results, may felt confused by the statement, leading to misinterpretations of the statement. In this study, we aim to re-examine the accuracy of the p-value and introduce an alternative way for testing the hypothesis. We conduct a simulation study to investigate the reliability of the p-value. Apart from investigating the performance of p-value, we also introduce some existing approaches, Minimum Bayes Factors and Belief functions, for replacing p-value. Results from the simulation study confirm unreliable p-value in some cases and that our proposed approaches seem to be useful as the substituted tool in the statistical inference. Moreover, our results show that the plausibility approach is more accurate for making decisions about the null hypothesis than the traditionally used p-values when the null hypothesis is true. However, the MBFs of Edwards et al. [Bayesian statistical inference for psychological research. Psychol. Rev. 70(3) (1963), pp. 193–242]; Vovk [A logic of probability, with application to the foundations of statistics. J. Royal Statistical Soc. Series B (Methodological) 55 (1993), pp. 317–351] and Sellke et al. [Calibration of p values for testing precise null hypotheses. Am. Stat. 55(1) (2001), pp. 62–71] provide more reliable results compared to all other methods when the null hypothesis is false. [ABSTRACT FROM AUTHOR]

Although choosing between several alternatives is the basic and most common process of decision-making, it has been well established that when having to decide, people are prone to various biases and seldom elect an alternative rationally. One of the most common and well-researched biases is the 'choice-bias' and many researches demonstrated its effect on decision-makers (both high-level and daily decisions) of the previous generations. This research examined the hypothesis that since the psychological development of 'generation Y' differs significantly from the researched generations, youth today are more resistant to this specific bias. A lifetime of constant exposure to the overabundance of suggestions and opportunities may have influenced decision-making capabilities. A study conducted on two separate groups of students (256 participants) revealed that no choice bias was observed, unlike similar studies conducted with previous generation populations. [ABSTRACT FROM AUTHOR]

Statistical methods are indispensable to the practice of science. But statistical hypothesis testing can seem daunting, with P-values, null hypotheses, and the concept of statistical significance. This article explains the concepts associated with statistical hypothesis testing using the story of "the lady tasting tea," then walks the reader through an application of the independent-samples t-test using data from Peter and Rosemary Grant's investigations of Darwin's finches. Understanding how scientists use statistics is an important component of scientific literacy, and students should have opportunities to use statistical methods like this in their science classes. [ABSTRACT FROM AUTHOR]

This study compares husbands' and wives' views on the person in a couple who should be responsible for preparing for hurricane hazards; it also examines whether the varying levels of agreement reached by husbands and wives regarding this responsibility are associated with actual preparedness behaviors. An online survey targeting married, heterosexual couples living in Sarasota County, Florida, USA was sent out between March and May, 2015. Both the husbands and the wives were asked to fill out the survey. A total of 170 surveys were used for analysis. Results suggested that husbands and wives felt that they had shared responsibility for most of the 19 preparedness behaviors considered. However, a few stereotypically masculine preparedness behaviors were found to typically fall to husbands. Husbands' and wives' views of perceived responsibility were not statistically different, but husbands tended to favor individual responsibility, while wives tended to favor joint responsibility. Higher levels of agreement were significantly associated with greater engagement in planning-related preparedness behaviors. Policy implications are discussed. [ABSTRACT FROM AUTHOR]

Two rationales have emerged for why individuals keep their promises: (a) an emotional commitment to keep actions and words consistent, a commitment rationale and (b) avoidance of guilt due to not meeting the expectations of the promisee, an expectations rationale. We propose a new dichotomy with clearer distinctions between rationales: (1) an internal consistency rationale, which is the desire to keep actions and words consistent regardless of others' awareness of the promise and (2) a communication rationale, which captures all aspects of promise keeping that are associated with the promisee having learned of the promise, including but not limited to promisee expectations. Using an experiment that manipulates whether promises are delivered, we find no support for the internal consistency rationale; only delivered promises are relevant. In a second experiment designed to better understand what aspect of promise delivery influences promisor behavior, we manipulate whether the promise is delivered before or after the promisee is able to take a trusting action. We find late-arriving promises are relevant though not as relevant as promises delivered before the promisee chooses whether to take the trusting action. We conclude that implicit contracting does not fully explain promise keeping, because had it done so, late-arriving promises would also be irrelevant. [ABSTRACT FROM AUTHOR]

Predicting and analyzing behaviors of investors is of great value to financial institutions. This paper uses survey data from about 9,000 individual investors across China to explore the predictability of decision behaviors by studying demographic characteristics that are relatively easy to obtain. After applying Pearson’s chi-squared test, Spearman rank correlation test, and several data mining methods, we verified that demographic characteristics are closely linked to decision behaviors, and it would be an economical and feasible solution for financial organizations to build initial behavioral prediction models especially when investors’ behavioral data are insufficient. [ABSTRACT FROM AUTHOR]

An important theoretical question in decision making concerns the nature of cue-generation: What mechanism drives the generation of cues used to make inferences? Most models of decision making assume that the properties of cues, often cue validity, initiate a set of dynamic pre-decision processes. In two studies, we test how memory accessibility affects cue use by manipulating both ecological cue validity and cue accessibility in a stock-forecasting task. Cue accessibility was manipulated by the pattern of accurate cue discriminations within experiment blocks of the learning phase of the experiments. Specifically, we manipulated the serial positions in which the cues accurately discriminated while holding overall cue validity constant. At test, participants preferred cues that discriminated early in the learning phase—a kind of primacy effect. The findings suggest that cue use is influenced by memory retrieval mechanisms and that cue use is not solely determined by cue validity. The results have implications for the development of computational models of heuristic decision-making. [ABSTRACT FROM AUTHOR]

Aims: To clarify the hypothesis tests associated with the full covariate modelling (FCM) approach in population pharmacokinetic analysis, investigate the potential impact of multiplicity in population pharmacokinetic analysis, and evaluate simultaneous confidence intervals (SCI) as an approach to control multiplicity. Methods: Clinical trial simulations were performed using a simple one‐compartment pharmacokinetic model. Different numbers of covariates, sample sizes, effect sizes of covariates, and correlations among covariates were explored. The false positive rate (FPR) and power were evaluated. Results: The FPR for the FCM approach dramatically increases with number of covariates. The chance of incorrectly selecting ≥1 seemingly clinically relevant covariates can be increased from 5% to a 40–70% range for 10–20 covariates. The SCI approach may provide appropriate control of the family‐wise FPR, allowing more appropriate decision making. As a result, the power detecting real effects without incorrectly identifying non‐existing effects can be greatly improved by the SCI approach compared to the approach in current practice. The performance of the SCI approach is driven by the ratio of sample size to number of covariates. The FPR can be controlled at 5% and 10% using the SCI approach when the ratio was ≥20 and 10, respectively. Conclusion: The FCM approach still lies within the framework of statistical testing, and therefore multiplicity is an issue for this approach. It is imperative to consider multiplicity reporting and adjustments in FCM modelling practice to ensure more appropriate decision making. [ABSTRACT FROM AUTHOR]

Quantifying the uncertainty in hydrological forecasting is valuable for water resources management and decision-making processes. The hydrological uncertainty processor (HUP) can quantify hydrological uncertainty and produce probabilistic forecasts under the hypothesis that there is no input uncertainty. This study proposes a HUP based on a copula function, in which the prior density and likelihood function are explicitly expressed, and the posterior density and distribution obtained using Monte Carlo sampling. The copula-based HUP was applied to the Three Gorges Reservoir, and compared with the meta-Gaussian HUP. The Nash-Sutcliffe efficiency and relative error were used as evaluation criteria for deterministic forecasts, while predictive QQ plot, reliability, resolution and continuous rank probability score (CRPS) were used for probabilistic forecasts. The results show that the proposed copula-based HUP is comparable to the meta-Gaussian HUP in terms of the posterior median forecasts, and that its probabilistic forecasts have slightly higher reliability and lower resolution compared to the meta-Gaussian HUP. Based on the CRPS, both HUPs were found superior to deterministic forecasts, highlighting the effectiveness of probabilistic forecasts, with the copula-based HUP marginally better than the meta-Gaussian HUP. [ABSTRACT FROM PUBLISHER]

Maternal capabilities-qualities of mothers that enable them to leverage skills and resources into child health-hold potential influence over mother's adoption of child caring practices, including infant and young child feeding. We developed a survey ( n = 195) that assessed the associations of 4 dimensions of maternal capabilities (social support, psychological health, decision making, and empowerment) with mothers' infant and young child feeding practices and children's nutritional status in Uganda. Maternal responses were converted to categorical subscales and an overall index. Scale reliability coefficients were moderate to strong (α range = 0.49 to 0.80). Mothers with higher social support scores were more likely to feed children according to the minimum meal frequency (odds ratio [OR] [95% confidence interval (CI)] = 1.38 [1.10, 1.73]), dietary diversity (OR [95% CI] = 1.56 [1.15, 2.11]), iron rich foods, (OR [95% CI] = 1.47 [1.14, 1.89]), and minimally acceptable diet (OR [95% CI] = 1.55 [1.10, 2.21]) indicators. Empowerment was associated with a greater likelihood of feeding a minimally diverse and acceptable diet. The maternal capabilities index was significantly associated with feeding the minimum number of times per day (OR [95% CI] = 1.29 [1.03, 1.63]), dietary diversity (OR [95% CI] = 1.44 [1.06, 1.94]), and minimally acceptable diet (OR [95% CI] = 1.43 [1.01, 2.01]). Mothers with higher psychological satisfaction were more likely to have a stunted child (OR [95% CI] = 1.31 [1.06, 1.63]). No other associations between the capabilities scales and child growth were significant. Strengthening social support for mothers and expanding overall maternal capabilities hold potential for addressing important underlying determinants of child feeding in the Ugandan context. [ABSTRACT FROM AUTHOR]

A typical rule that has been used for the endorsement of new medications by the Food and Drug Administration is to have two trials, each convincing on its own, demonstrating effectiveness. “Convincing” may be subjectively interpreted, but the use of p-values and the focus on statistical significance (in particular with p < .05 being coined significant) is pervasive in clinical research. Therefore, in this paper, we calculate with simulations what it means to have exactly two trials, each with p < .05, in terms of the actual strength of evidence quantified by Bayes factors. Our results show that different cases where two trials have a p-value below .05 have wildly differing Bayes factors. Bayes factors of at least 20 in favor of the alternative hypothesis are not necessarily achieved and they fail to be reached in a large proportion of cases, in particular when the true effect size is small (0.2 standard deviations) or zero. In a non-trivial number of cases, evidence actually points to the null hypothesis, in particular when the true effect size is zero, when the number of trials is large, and when the number of participants in both groups is low. We recommend use of Bayes factors as a routine tool to assess endorsement of new medications, because Bayes factors consistently quantify strength of evidence. Use of p-values may lead to paradoxical and spurious decision-making regarding the use of new medications. [ABSTRACT FROM AUTHOR]

Many people exhibit inconsistent preferenceswhen theymake choices based on descriptive summaries as compared to choices based on prior experiences. Theoretically, factors that promote more deliberative and skilled decision making (e.g., statistical numeracy) should also tend to promote more consistent choices and preferences regardless of information presentation formats. To test this hypothesis, in two studies I investigated individual differences in information search strategies (e.g., the amount and direction of information search) while estimating the degree to which numeracy predicted risky choice consistency across (a) decisions-from-description and (b) the decisions-from-samples. Results from Study 1 revealed that numeracy was generally associated with more extensive sampling and greater choice consistency across paradigms. Instead of reflecting differences in logical maximizing strategies (e.g., calculating expected values), analyses indicated that highly-numerate participants largely generated consistent choices by relying on heuristic-type processes (e.g., alternated between options less and exploring options with higher outcome variability more). In Study 2, the relationship between numeracy and choice consistency was eliminated when all participants were forced to make choices after experiencing the same fixed amount of sampling (i.e., provided the same amount of information). Taken together, the results of both studies converge with and extend previous findings (e.g., Skilled Decision Theory), indicating that numerate participants may generally exhibit more consistent preferences and choices via deliberatative heuristic search during decision making. [ABSTRACT FROM AUTHOR]

The current investigation extended past efforts on cultural differences in sport fandom by investigating sport fandom in Qatar, a previously unexplored culture. A sample of 259 sport fans completed a questionnaire packet assessing demographic variables, sport fandom, team identification, impacts of various socialization agents, and six typical sport fan behaviors. The results revealed a number of interesting findings including gender differences (males exhibited both greater levels of identification with a team and sport fandom than females), the influence of team-related factors for selecting a sport team, and a particularly large percentage of foreign teams listed as one's favorite team. To further our understanding of the behavior of sport fans globally and provide insights to sport managers, the results of this research are compared and contrasted with similar studies conducted in Australia, Greece, Norway, U.K., and the U.S. [ABSTRACT FROM AUTHOR]

We implemented a Choice Blindness Paradigm containing political statements in Argentina to reveal the existence of categorical ranges of introspective reports, identified by confidence and agreement levels, separating easy from very hard to manipulate decisions. CBP was implemented in both live and web-based forms. Importantly, and contrary to what was observed in Sweden, we did not observe changes in voting intentions. Also, confidence levels in the manipulated replies where significantly lower than in non-manipulated cases even in undetected manipulations. We name this phenomenon unconscious detection of self-deception. Results also show that females are more difficult to manipulate than men. [ABSTRACT FROM AUTHOR]

The presence of institutional investors may change the behaviors of companies. The impact of institutional investors on management decisions on financial affairs have been proven in other studies; yet, the present study aims to investigate the relationship between lack of information symmetry an concentration of proprietorship with profit management in the companies listed in Tehran Stock Exchange. The period under study included years 2004 to 2009. Rahavard Novin Computer application was utilized to collect the data; then they were calculated using Microsoft Excel. SPSS computer application was used to test research hypothesis and conduct other statistical analysis using statistical methods like descriptive statistics, correlation (correlation coefficient, coefficient of determination), regression analysis and testing its coefficients, correlation analysis and test of coefficients and significance of the difference between two correlation coefficients. A total of 109 active companies in the stock exchange were selected as the sample of the study. Results on the first hypothesis revealed that the relationship between concentration of proprietorship and lack of information symmetry. In case of the second hypothesis, it is predicted that there is a significant relationship between profit management with lack of information symmetry and concentration of proprietorship. According to research results, investors and analysts ought to pay attention to factors like proprietorship composition, the level of information symmetry along with the figures published by the companies when making short and long-term decisions. [ABSTRACT FROM AUTHOR]

Previous researches support that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Moreover, literature shows that different types of graphical information can help or harm the accuracy on decision making of accountants and financial analysts. We conducted a 4×2 mixed-design experiment to examine the effects of numerical information disclosure on financial analysts’ accuracy, and investigated the role of overconfidence in decision making. Results show that compared to text, column graph enhanced accuracy on decision making, followed by line graphs. No difference was found between table and textual disclosure. Overconfidence harmed accuracy, and both genders behaved overconfidently. Additionally, the type of disclosure (text, table, line graph and column graph) did not affect the overconfidence of individuals, providing evidence that overconfidence is a personal trait. This study makes three contributions. First, it provides evidence from a larger sample size (295) of financial analysts instead of a smaller sample size of students that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Second, it uses the text as a baseline comparison to test how different ways of information disclosure (line and column graphs, and tables) can enhance understandability of information. Third, it brings an internal factor to this process: overconfidence, a personal trait that harms the decision-making process of individuals. At the end of this paper several research paths are highlighted to further study the effect of internal factors (personal traits) on financial analysts’ accuracy on decision making regarding numerical information presented in a graphical form. In addition, we offer suggestions concerning some practical implications for professional accountants, auditors, financial analysts and standard setters. [ABSTRACT FROM AUTHOR]

In this study, we conducted a laboratory experiment to assess preemptive striking by and towards individuals or groups. In the framework of a preemptive strike game, we set the following four conditions: one person faced another person, one person faced a three-person group, a three-person group faced an individual, and a three-person group faced another three-person group. Previous studies have revealed that greed is activated when participants belong to a group, while fear is activated when participants interact with a group, and further, that attacking behaviors in the preemptive strike game are driven by fear. These observations led to a hypothesis that high attack rates would be realized when participants interact with a group, regardless of whether the participants make decisions as individuals or a group. The results of our experiment, however, rejected this hypothesis. Among the four conditions, the attack rate was highest when a three-person group faced an individual. As possible reasons for our observation, we discuss the potential threat stemming from the imbalance in the effectiveness of attack between individuals and groups, and the (incorrect) belief by groups that single individuals would be more likely to attack out of fear. [ABSTRACT FROM AUTHOR]

This paper presents a Multi-Hypotheses Tracking (MHT) approach that allows solving ambiguities that arise with previous methods of associating targets and tracks within a highly volatile vehicular environment. The previous approach based on the Dempster–Shafer Theory assumes that associations between tracks and targets are unique; this was shown to allow the formation of ghost tracks when there was too much ambiguity or conflict for the system to take a meaningful decision. The MHT algorithm described in this paper removes this uniqueness condition, allowing the system to include ambiguity and even to prevent making any decision if available data are poor. We provide a general introduction to the Dempster–Shafer Theory and present the previously used approach. Then, we explain our MHT mechanism and provide evidence of its increased performance in reducing the amount of ghost tracks and false positive processed by the tracking system. [ABSTRACT FROM AUTHOR]

Cluster interpretation is an important step for a proper understanding of a set of classes, independently of whether they have been automatically discovered or expert-based. An understanding of classes is crucial for the further use of classes as the basis of a decision-making process. The abundant work on cluster validity found in the literature is mainly focused on the validation of clusters from the structural point of view. However, structural validation does not ensure that the clustering is useful, since meaningfulness is the key to guaranteeing that classes can support further decisions. In previous works, special significance tests taken from the field of multivariate analysis were introduced in an interpretation methodology for automatically assessing relevant variables in particular classes. In this paper, we present the interpretation of nested partitions and the relationships between both interpretations are studied. In particular, the inconsistencies produced in interpretation when a second partition refines the first one with a higher level of granularity are studied, diagnosed, and a modification of the original methodology is provided to guarantee consistency in these cases. The relevant characteristics detected in a parent class must also be inherited in subclasses, or at least in some of them. The proposal is evaluated using a real data set on baseline health conditions and dietary habits of a sample of the general population. [ABSTRACT FROM AUTHOR]

What explains cooperation in international environmental networks? What are the effects of skills and money on the decision by state agencies to collaborate across borders on environmental problems? This article answers these questions, showing that international cooperation provides environmental bureaucrats and their agencies with the opportunity to pool scarce resources, update critical skills, and attract funds from international donors. Theory and results offer novel findings on network homophily (the tendency of similar actors to work together), as international cooperation increases between environmental state agencies at similar levels of program development. Hypotheses are tested using social network analysis to measure cooperation on a dataset that includes all regional and global grants awarded over the past two decades by the Global Environment Facility (GEF). [ABSTRACT FROM AUTHOR]

The article presents the study that explores on the use of haematopoietic stem cell transplantation (SCT) in the treatment of Fanconi anemia (FA) patients in Canada and the U.S. The topics discussed include the attributes of FA, the factors that influenced the decision making of FA patients and family members on SCT, and the benefits and probable risks of SCT.

More than 500,000 children sustain a traumatic brain injury (TBI) each year. Previous studies have described significant variation in inhospital mortality after pediatric TBI. The aim of this study was to identify facility-level characteristics independently associated with 30-day inhospital mortality after pediatric severe TBI. We hypothesized that, even after accounting for patient-level characteristics associated with mortality, the characteristics of facilities where patients received care would be associated with inhospital mortality. Using data from the National Trauma Data Bank from 2009-2012, we identified a cohort of 6707 pediatric patients hospitalized with severe TBI in 391 facilities and investigated their risk of 30-day inhospital mortality. Pre-specified facility-level characteristics (trauma certification level, teaching status, census region, facility size, nonprofit status, and responsibility for pediatric trauma care) were added to a Poisson regression model that accounted for patient-level characteristics associated with mortality. In multivariable analyses, patients treated in facilities located in the Midwest (risk ratio [RR]=1.42; 95% confidence interval [CI] 1.12-1.81) and South (RR=1.39; 95% CI: 1.12-1.72) regions had higher likelihoods of 30-day inhospital mortality compared with patients treated in the Northeast. Other facility-level characteristics were not found to be significant. To our knowledge, this is one of the largest investigations to identify regional variation in inhospital mortality after pediatric severe TBI in a national sample after accounting for individual and other facility-level characteristics. Further investigations to help explain this variation are needed to inform evidence-based decision-making for pediatric severe TBI care across different settings. [ABSTRACT FROM AUTHOR]

Highlights: [•] Apply semantic analysis on internet data to identify weak signals. [•] Project further data into semantic subspace to identify weak signal time series. [•] Compare time series to given hypotheses. [•] Provide relevant weak signal developments to decision makers. [Copyright &y& Elsevier]