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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]

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]

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]

Parents may increase the probability of offspring survival by choosing suitable rearing sites where risks are as low as possible. Predation and competition are major selective pressures influencing the evolution of rearing site selection. Poison frogs look after their clutches and deposit the newly hatched tadpoles in bodies of water where they remain until metamorphosis. In some species, cannibalism occurs, so parents deposit their tadpoles singly in very small pools. However, cannibalism also occurs in species that deposit tadpoles in larger pools already occupied by heterospecific or conspecific larvae that could be either potential predators or competitors. Here, I test the hypothesis that, given the choice, males of Dendrobates tinctorius would deposit their newly hatched tadpoles in low-risk sites for their offspring. I characterised the pools used by D. tinctorius for tadpole deposition, conducted experiments to determine the larval traits that predict the occurrence of and latency to cannibalism, and tested whether parents deposit their tadpoles in low-risk pools. I found that (1) neither pool capacity nor the presence of other larvae predict the presence/absence or number of tadpoles; (2) cannibalism occurs often, and how quickly it occurs depends on the difference in size between the tadpoles involved; and (3) the likelihood of males depositing their tadpoles in occupied pools increases with the size of the resident tadpole. I suggest that predation/cannibalism is not the only factor that parents assess when choosing deposition sites, and that the presence of larger conspecifics may instead provide information about pool quality and stability. [ABSTRACT FROM AUTHOR]

This paper considers a collaborative human decision making framework in which local decisions made at the individual agents are combined at a moderator to make the final decision. More specifically, we consider a binary hypothesis testing problem in which a group of n people makes individual decisions on which hypothesis is true based on a threshold based scheme and the thresholds are modeled as random variables. We assume that, in general, the decisions are not received by the moderator perfectly and the communication errors are modeled via a binary asymmetric channel. Assuming that the moderator does not have the knowledge of exact values of thresholds used by the individual decision makers but has probabilistic information, the performance in terms of the probability of error of the likelihood ratio based decision fusion scheme is derived when there are two agents in the decision making system. We show that the statistical parameters of the threshold distributions have optimal set of values which result in the minimum probability of error and we analytically derive these optimal values under certain conditions. We further provide detailed performance comparison to the case where the likelihood ratio based decision fusion is performed at the moderator with exact knowledge of the thresholds used by individual agents. For an arbitrary number of human agents n(> 2), we derive the performance of decision fusion with majority rule using certain approximations when the individual thresholds are modeled as random variables. [ABSTRACT FROM PUBLISHER]

Background: Recent frameworks for understanding food rewards recognize the role of separable affective and motivational processes (liking and wanting) in driving human eating behavior. Separate assessments of liking and wanting may aid in understanding the complex eating-related behaviors seen in anorexia nervosa (AN). Objective: The aim of this study was to examine separately liking and wanting for foods of different energy densities in women at different stages of AN and in healthy volunteers at both an implicit and an explicit level. Design: Explicit liking and wanting responses to high- and low-calorie foods were derived from analog ratings, whereas an implicit "wanting" measure was identified by using reaction time in a forced-choice procedure. Explicit and implicit processes were compared across 3 groups of AN participants (current AN, weight-restored AN, and recovered AN) and healthy volunteers. Results: Currently underweight AN participants explicitly wanted high-calorie foods less than did the other groups. Both current and weight-restored AN groups demonstrated significantly less implicit "wanting" for high-calorie foods and more implicit "wanting" for low-calorie foods--an inverted pattern to never-ill participants. Conclusions: The aberrant responses to food that characterize AN may be driven more by altered motivational salience ("wanting") than by explicit liking responses. This pattern of aberrant food reward appears to be independent of weight status. Examining the processes that motivate approach or avoidance of low- and high-calorie foods in AN may aid the development of targeted strategies to augment existing interventions. [ABSTRACT FROM AUTHOR]

This paper studies the quantization of prior probabilities, drawn from an ensemble, in distributed detection with data fusion by combination of binary local decisions. Design and performance equivalences between a team of N agents and a more powerful single agent are obtained. Effects of identical quantization and diverse quantization on mean Bayes risk are compared. It is shown that when agents using diverse quantizers interact to agree on a perceived common risk, the effective number quantization levels is increased. With this collaboration, optimal diverse regular quantization with K cells per quantizer performs as well as optimal identical quantization with N(K-1)+1 cells per quantizer. Similar results are obtained for the maximum Bayes risk error criterion. [ABSTRACT FROM PUBLISHER]

We study the detection error probability associated with a balanced binary relay tree, where the leaves of the tree correspond to N identical and independent sensors. The root of the tree represents a fusion center that makes the overall detection decision. Each of the other nodes in the tree is a relay node that combines two binary messages to form a single output binary message. Only the leaves are sensors. In this way, the information from the sensors is aggregated into the fusion center via the relay nodes. In this context, we describe the evolution of the Type I and Type II error probabilities of the binary data as it propagates from the leaves toward the root. Tight upper and lower bounds for the total error probability at the fusion center as functions of N are derived. These characterize how fast the total error probability converges to 0 with respect to N, even if the individual sensors have error probabilities that converge to 1/2. [ABSTRACT FROM PUBLISHER]

Judgment and decision making research overwhelmingly uses null hypothesis significance testing as the basis for statistical inference. This article examines an alternative, Bayesian approach which emphasizes the choice between two competing hypotheses and quantifies the balance of evidence provided by the data--one consequence of which is that experimental results may be taken to strongly favour the null hypothesis. We apply a recently-developed "Bayesian t-test" to existing studies of the anchoring effect in judgment, and examine how the change in approach affects both the tone of hypothesis testing and the substantive conclusions that one draws. We compare the Bayesian approach with Fisherian and Neyman-Pearson testing, examining its relationship to conventional p-values, the influence of effect size, and the importance of prior beliefs about the likely state of nature. The results give a sense of how Bayesian hypothesis testing might be applied to judgment and decision making research, and of both the advantages and challenges that a shift to this approach would entail. [ABSTRACT FROM AUTHOR]

It is common practice to treat coverage probability as the only requirement for interval estimation. This allows the use of one-sided confidence intervals. These achieve their coverage probabilities by including parameter values with relative likelihood approaching 0. This violates the law of likelihood, a post-data concept of statistical evidence introduced by Ronald Fisher in 1921. Coverage probability and the law of likelihood are both necessary for interval estimation, but neither is sufficient. When combined, they minimize the possibility of users with the same data, model, and confidence level getting different answers. [ABSTRACT FROM AUTHOR]

Personal, or subjective, probabilities are used as inputs to many inferential and decision-making models, and various procedures have been developed for the elicitation of such probabilities. Included among these elicitation procedures are scoring rules, which revolve the computation of a score based on the assessor's stated probabilities and on the event that actually occurs. The development of scoring rules has, in general, been restricted to the elicitation of discrete probability distributions. In this paper, families of scoring rules for the elicitation of continuous probability distributions are developed and discussed. [ABSTRACT FROM AUTHOR]

A double sample test for a hypothesis concerning the mean mu of a normal random variable with unknown variance sigma[sup 2] is presented in this note. This test is an alternative to the usual single sample t test and is made by taking samples at two stages. After the first sample has been observed the hypothesis is rejected, accepted or a second sample is taken. This double sample test is a modification of a double sample test suggested by D. Owen. However, for the test being suggested here if the second sample is taken the information from the first sample is used in making the final decision. A table is included which is a tabulation of the rejection and acceptance points for various sample sizes and alpha = .05 and alpha = .01. Additional tables are included which give some power values and expected sample sizes for the new test and Owen's test. These power values are compared with power values of various single sample t tests. Conclusions about desirable sample sizes are presented for both the new test and Owen's test. [ABSTRACT FROM AUTHOR]

In an earlier paper [5] the authors compared the power of the BLUS test with the probability of a correct decision of the Durbin-Watson bounds test. A method to compute the distribution of the Von Neumann ratio under the null hypothesis and under the alternative hypothesis was given. In the present paper the latter method is used to tabulate the BLUS-test statistic and to compute the exact significance points of the Durbin-Watson test for several examples. Powers of both tests are computed and compared. It appears that, for the cases considered, the power of the exact Durbin-Watson test exceeds that of the BLUS procedure, while the latter is greater than the probability of a correct decision in the Durbin-Watson bounds test. [ABSTRACT FROM AUTHOR]

The problem of iterated tests of hypotheses has been treated from the standpoint of multiple decision theory. Under the assumption that there is a UMP test (not necessarily similar) for each component hypothesis, a procedure has been developed which ensures an upper bound for various probabilities of misclassification and which maximizes the probabilities of correct classification in some class. [ABSTRACT FROM AUTHOR]

In hypothesis testing, the level of significance, α, often performs a screening as well as an evaluating function. Results which are not "significant" at some preset value of α are simply not reported. Unfortunately, this value of α is usually arbitrarily set at .05 or .01 and bears no relation to the needs of potential users of the study. This paper suggests an approach to making the selection of α more responsive to these potential applications. [ABSTRACT FROM AUTHOR]

In evaluating decision alternatives that involve risk of death among members of the public, there are two types of equity that must be considered, namely, ex ante and ex post equity. Among the two, ex ante equity is more controversial. This paper suggests refinements to recent definitions of ex ante equity, based on distribution of individuals' risks across equally desirable outcomes, and historical inequity. [ABSTRACT FROM AUTHOR]