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Introduction: Simon's design has been widely used in oncology to conduct single arm phase II trials and to make Go/No-Go development decision. Other authors have proposed designs with decision-making frameworks that include a third, "Consider" outcome. For results in the Consider zone, a final Go/No-Go development decision must still be made; however it is typically a subjective decision based on the totality of data and the development landscape. Under this framework, the probability of continuing development when the candidate therapy is truly ineffective or the probability of stopping development when the candidate therapy is truly effective is undefined. Methods: We use a motivating example to compare end of trial decision-making between Simon's two-stage approach and a Multilevel outcome approach. We present the minimum and maximum development decision error probabilities by varying whether candidates that end in the Consider zone would ultimately continue with development or not. Results: The Multilevel approach typically requires fewer patients, but the risk of making an incorrect drug development decision is inflated above the statistically defined Type I and Type II error rates. Compared to a Type I error rate of 20%, the Multilevel trial's maximum probability of moving forward with an ineffective therapy is 22%, 27%, and 36% for Consider zone sizes of 10%, 20%, and 30%, respectively. Conclusion: The Multilevel approach provides flexibility in interpreting moderate efficacy results. However, the flexibility is accomplished with a lower sample size and corresponding uncertainty in the trial outcome that increases the risk of incorrect drug development decisions. [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]

Evidence-based medicine frequently uses statistical hypothesis testing. In this paradigm, data can only disconfirm a research hypothesis' competitors: One tests the negation of a statistical hypothesis that is supposed to correspond to the research hypothesis. In practice, these hypotheses are often misaligned. For instance, directional research hypotheses are often paired with non-directional statistical hypotheses. Prima facie, one cannot gain proper evidence for one's research hypothesis employing a misaligned statistical hypothesis. This paper sheds lights on the nature of and the reasons for such misalignments and it provides a thorough analysis of whether they pose a threat to evidence-based medicine. The upshots are that the misalignments are often hidden for clinicians and that although some cases of misalignments can be partially counterbalanced, the overall threat is non-negligible. The counterbalances either lead to methodological inadequacy (in addition to the misalignment), loss of statistical power, or involve a (potential) lack of information that could be crucial for decision making. This result casts doubt on various findings of medical studies in addition to issues associated with under-powered studies or the replication crisis. [ABSTRACT FROM AUTHOR]

The present work is aimed to extend the classical statistical methods based on intuitionistic fuzzy data to hypothesis test about exact parameter of the underlying population. In this approach, the concepts of the intuitionistic fuzzy type-I error, intuitionistic fuzzy type-II error, intuitionistic fuzzy power and intuitionistic fuzzy p value are extended at a given significance level. A degree-based criterion is also suggested to compare the intuitionistic fuzzy p value and a specific significance level to make decision on whether accepting or rejecting the null hypothesis. An applied example is examined based on the proposed method in both parametric and nonparametric cases. The results indicate that the proposed method can be successfully applied for all parametric/nonparametric statistical hypotheses testing based on intuitionistic fuzzy continuous data. [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]

This paper estimates the cost efficiency of 81 general hospitals in the Czech Republic during 2006-2010. We employ the conditional order-m approach to assess how inpatient costs in a hospital translate to inpatient outputs considering its environmental characteristics. The outputs include quantitative indicators such as (i) acute patients adjusted for DRG case-mix index, (ii) nursing patients, and (iii) publications reflecting research activity of a hospital; but also a qualitative indicator (iv) nurses/bed ratio. Nonprofit hospitals, university hospitals, and hospitals with specialized centers are generally less efficient. [ABSTRACT FROM AUTHOR]

In this paper, a method is proposed for testing statistical hypotheses about the fuzzy parameter of the underlying parametric population. In this approach, using definition of fuzzy random variables, the concept of the power of test and p value is extended to the fuzzy power and fuzzy p value. To do this, the concepts of fuzzy p value have been defined using the $$\alpha $$ -optimistic values of the fuzzy observations and fuzzy parameters. This paper also develop the concepts of fuzzy type-I, fuzzy type-II errors and fuzzy power for the proposed hypothesis tests. To make decision as a fuzzy test, a well-known index is employed to compare the observed fuzzy p value and a given significance value. The result provides a fuzzy test function which leads to some degrees to accept or to reject the null hypothesis. As an application of the proposed method, we focus on the normal fuzzy random variable to investigate hypotheses about the related fuzzy parameters. An applied example is provided throughout the paper clarifying the discussions made in this paper. [ABSTRACT FROM AUTHOR]

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The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of 'researcher degrees of freedom.' This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework. [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]

We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., “sort by color”). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed. [ABSTRACT FROM AUTHOR]

Science traditionally is taught as a linear process based on logic and carried out by objective researchers following the scientific method. Practice of science is a far more nuanced enterprise, one in which intuition and passion become just as important as objectivity and logic. Whether the activity is committing to study a particular research problem, drawing conclusions about a hypothesis under investigation, choosing whether to count results as data or experimental noise, or deciding what information to present in a research paper, ethical challenges inevitably will arise because of the ambiguities inherent in practice. Unless these ambiguities are acknowledged and their sources understood explicitly, responsible conduct of science education will not adequately prepare the individuals receiving the training for the kinds of decisions essential to research integrity that they will have to make as scientists. [ABSTRACT FROM AUTHOR]

Most streaming decision models evolve continuously over time, run in resource-aware environments, and detect and react to changes in the environment generating data. One important issue, not yet convincingly addressed, is the design of experimental work to evaluate and compare decision models that evolve over time. This paper proposes a general framework for assessing predictive stream learning algorithms. We defend the use of prequential error with forgetting mechanisms to provide reliable error estimators. We prove that, in stationary data and for consistent learning algorithms, the holdout estimator, the prequential error and the prequential error estimated over a sliding window or using fading factors, all converge to the Bayes error. The use of prequential error with forgetting mechanisms reveals to be advantageous in assessing performance and in comparing stream learning algorithms. It is also worthwhile to use the proposed methods for hypothesis testing and for change detection. In a set of experiments in drift scenarios, we evaluate the ability of a standard change detection algorithm to detect change using three prequential error estimators. These experiments point out that the use of forgetting mechanisms (sliding windows or fading factors) are required for fast and efficient change detection. In comparison to sliding windows, fading factors are faster and memoryless, both important requirements for streaming applications. Overall, this paper is a contribution to a discussion on best practice for performance assessment when learning is a continuous process, and the decision models are dynamic and evolve over time. [ABSTRACT FROM AUTHOR]

Information search during decision-making may be influenced both by selective attention and by the criterion used for ceasing to search. When the items searched are themselves emotive, the affective state of the decision-maker may bias these search processes. If an automatic selective attention bias operates, it may produce mood-congruent effects irrespective of context; e.g., negative affect may focus attention on negative items of information. An alternative possibility, suggested by the mood-as-input model, is that the influence of affect on search may depend on how decision-makers understand their emotions within a given context. The present study tested predictions derived from relevant theories of affective bias, using feedback as a means to generate a context of success or failure. Hundred and sixty participants were required to access positive and negative items of information in choosing between different routes for a search-and-rescue mission. Outcomes of choices were manipulated experimentally, so that in one condition participants received mostly positive feedback, and in a second condition participants received mostly negative feedback. Results showed that the feedback manipulation influenced affect, but there was considerable variation in affective state within each condition. Associations between affect and information search were moderated by feedback condition. For example, positive affect was associated with more frequent sampling of positive information in the negative feedback condition, but the association reversed when feedback was positive. Findings were consistent with the mood-as-input hypothesis, but not with an automatic selective attention bias. Context may influence how the decision-maker interprets their affective state. [ABSTRACT FROM AUTHOR]

In a hypothesis comparison task involving quantifiable evidence, we investigated whether judgments of relative probability were affected by gradual evidence accumulation and by making a series of revised ratings, rather than a single final one. Each trial of our task required participants to rate the probability that a focal hypothesis, rather than its alternative, was correct. We manipulated (1) the strength of evidence supporting the focal hypothesis, (2) the strength of evidence supporting its alternative, and (3) whether that evidence was presented in three sequential portions (gradually accumulated evidence condition) or, instead, was all presented instantaneously (control condition). In a second experiment, we also manipulated (4) the number of successive ratings made within a trial with gradually accumulated evidence. Regardless of how many ratings were made per trial, gradual evidence accumulation increased the effects of evidence strength on ratings of relative probability. [ABSTRACT FROM AUTHOR]

Objective: To assess the effectiveness of health and nutrition program (NutriAlz) versus usual care on functional level in elderly people with dementia living at home, as well as on clinical practice related to nutrition and on the caregiver's burden. Design: Cluster randomized multi-centre study with one-year follow-up. Setting: 11 Alzheimer outpatients and day care centres (Barcelona, Spain). Participants: Nine hundred and forty six home-living Alzheimer patients with identified caregiver were consecutively recruited (intervention group: 6 centres, 448 patients vs control group: 5 centres, 498 patients). Intervention: The intervention was a teaching and training intervention on health and nutrition program, NutriAlz, directed both to physician and main caregiver, as well as persons affected by Alzheimer's disease or other dementias, including a standardised protocol for feeding and nutrition. Main Outcome Measures: The main outcome measure was the reduction in the loss of autonomy (Activities of daily living (ADL/IADL) scales) assessed at 6 and 12 months. Secondary outcomes measures were Improvement in nutritional status (Mini Nutritional Assessment (MNA), BMI, and weight changes), and caregiver burden (Zarit scale). Results: The one-year assessment was completed for 293 patients (65.4%) in the intervention group and 363 patients (72.9%) in the control group (usual care). The annual rate of ADL change was −0.83 vs −0.62 (p=0.984), and the caregiver's subjective burden 0.59 vs 2.36 (p=0.681) in intervention and control group, respectively. MNA, however, showed an improvement (+0.46 vs −0.66, p=0.028), suggesting an effective nutritional behaviour. Conclusion: The NutriAlz program had no effect on functional decline in Alzheimer disease patients living at home over one year, but reduced the risk for malnutrition, as recommendations concerning diet and exercise were provided. [ABSTRACT FROM AUTHOR]

This article concerns the prescriptive function of decision analysis. Consider an agent who must choose an action yielding welfare that varies with an unknown state of nature. It is often asserted that such an agent should adhere to consistency axioms which imply that behavior can be represented as maximization of expected utility. However, our agent is not concerned the consistency of his behavior across hypothetical choice sets. He only wants to make a reasonable choice from the choice set that he actually faces. Hence, I reason that prescriptions for decision making should respect actuality. That is, they should promote welfare maximization in the choice problem the agent actually faces. Any choice respecting weak and stochastic dominance is rational from the actualist perspective. [ABSTRACT FROM AUTHOR]

Potentially dynamically-inconsistent individuals create particular problems for economics, as their behaviour depends upon whether and how they attempt to resolve their potential inconsistency. This paper reports on the results of a new experiment designed to help us distinguish between the different types that may exist. We classify people into four types: myopic, naïve, resolute and sophisticated. We implement a new and simple experimental design in which subjects are asked to take two sequential decisions (interspersed by a random move by Nature) concerning the allocation of a given sum of money. The resulting data enables us to classify the subjects. We find that the majority are resolute, a significant few are sophisticated, rather few are naïve and similarly few are myopic. [ABSTRACT FROM AUTHOR]

The need to compare the distributions of directions of the discontinuities present in rock masses prompted the development of a new surrogate measure for non-parametric statistical tests. This is used to quantify the degree of matching between polymodal azimuth direction distributions determined from remotely sensed data for different areas and also between these and field measurements. The approach is based on an application of the Kolmogorov–Smirnov (K–S) goodness-of-fit test. However, in this application the main interest is to accept the null hypothesis (instead of rejecting it) so that there is a risk of committing a Type II statistical error when it is false, particularly if sample sizes are too small. Therefore, a method that employs a set of empirical criteria for calibrating the statistical decision was devised. The statistic used ( D ratio) provides a measure of the degree of reliability about the decision on whether or not to accept or reject the hypothesis. The methodology is tested and implemented using existing geological data and a tectonic model valid over a limited region, within which two study areas were taken for these developments. The results obtained indicate reasonable improvement of the performance of K–S tests for inferential purposes when empirical reliability criteria are used. This was acknowledged by increased matching between occurring and inferred discontinuities (tectonic structures) and reduction in rates of errors. Other applications envisaged include different data sources such as climate and soil data. [ABSTRACT FROM AUTHOR]

The paper is focused on regional redistribution of revenue of China and proposes to test two hypotheses. The first one is the positive relationship between inequality in the distribution of local fiscal situation and the central redistribution. The second one is a possible political channel of redistribution: the median voter hypothesis. Both hypotheses are confirmed empirically by the study. Therefore the median voter hypothesis is helpful for analyzing the redistribution to narrow the regional disparities of local expenditure among provinces, although there is no formal voting process on regional redistribution. In the process of decision-making in China, regional preference can be expressed sufficiently without voting actions. Thus Representative Democracy might not be a prerequisite for Median Voter Hypothesis in the case of China. [ABSTRACT FROM AUTHOR]

This paper explores the relationship of various trait emotions to the ethical choices of 189 college students who completed a managerial decision-making task as part of an in-basket exercise in a laboratory setting. Prior research regarding emotion influences on ethical decision-making and linkages between emotions and cognition informed hypotheses about how different types of emotions impact ethical choices. Findings supported our expectations that positive and negative emotions classified as active would be more strongly related to interpersonally-directed ethical choices than to organizationally-directed ones, and that passive emotions would be less related to ethical choices than active emotions. Implications for ethical decision-making research and organizational practices are discussed. [ABSTRACT FROM AUTHOR]

Strategy descriptions like the "Take The Best''-heuristic (G. Gigerenzer et al., 1991), the weighted additive rule, and the equal weight decision rule are competing theories about information integration in multi-attribute decision tasks. Behavioral decision research is confronted with the problem of drawing conclusions about unobservable decision strategies from behavioral data. Although there has been considerable progress due to methodical traditions like 'Structural Modeling' and 'Process Tracing', these paradigms have certain limitations in testing specific hypotheses about individual strategies. Some of these problems are summarized briefly. A deductive method for classifying individual response patterns is introduced. Predictions about regression coefficients are deduced from competing substantial hypotheses about strategies for decision making. These can be tested at the level of individual participants. The validity of this classification procedure is demonstrated with a Monte Carlo simulation. Some useful applications of the method are described, limitations of the method and potential generalizations are discussed. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the applicability of an extension of the Analytic Hierarchy Process (AHP) for personnel selection and placement. In line with the AHP approach, personnel selection is viewed as a multiple criteria-decision making situation. A personnel package, based on the analytic hierarchy theory, is suggested. The paper concludes with an evaluation of the suitability of the package as an aid for personnel decision-making. [ABSTRACT FROM AUTHOR]

This article reviews the statistical measures of association for the triple dichotomy. In three-variate analysis, the most interesting case occurs when the relation between variables A and B is controlled for a third one variable C, or antecedent variable. A and B are the original variables; a coefficient which is followed by AB is a zero-order coefficient; a coefficient which is followed by AB. C is a first-order coefficient referred to the AB relation when variable C is controlled. Statistics have for a long time ignored the distinction between symmetrical and asymmetrical relations. This has not produced serious consequences for bivariate relations except if an inferential interpretation was sought. The problem can be solved by paying greater attention to the hypothesized relations, and choosing the coefficient accordingly. After all, the choice is very simple: a relation can be symmetrical or asymmetrical. The range of possible relations between three variables is much greater: first, all relations are symmetric. Second, all relations are asymmetric; problems arise as regards which of the variables is the dependent one in the three bivariate relations. The possible combinations are eight. Third, some relations are symmetrical and some are asymmetrical. The possible combinations are eighteen.