Tests of sphericity of normal distributions and the analysis of repeated measures designs

The locally best invariant test statistic for testing sphericity of normal distributions is shown to be a simple function of the Box/Geisser-Greenhouse degrees of freedom correction factor in a repeated measures design. Because of this relationship it provides a more intuitively appealing test of the necessary and sufficient conditions for valid F-tests in repeated measures analysis of variance than the likelihood ratio test. The properties of the two tests are compared and tables of the critical values of the Box/Geisser-Greenhouse correction factor are given.     

The impact of using forced decision-making strategies on post-decisional confidence

The impact of motivational and cognitive factors on post-decisional confidence (PDC) level was tested in two experiments. In the first experiment, subjects were first identified as having an intuitive preference toward using either a compensatory or a noncompensatory decision strategy and later on were forced to use either a compatible or a non-compatible strategy. PDC level decreased after using a noncompensatory strategy, and the decrease was higher when it was a noncompatible strategy. In a second experiment, subjects received feedback about their preferred strategy but were not later forced to use any specific strategy. Most subjects continued to utilize their preferred strategy and PDC level was not changed. Overall, intuitive PDC was not found to be sensitive to differences between compensatory and noncompensatory strategies. The result suggested that PDC is a function of an internal cost-benefit analysis which includes both cognitive and motivational factors.     

创新期望差距与团队突破性创新：自我调节理论视角

本研究以自我调节理论为基础, 探讨团队领导的创新期望差距推进团队突破性创新的过程。根据实验结果以及一项多时点、多来源的问卷调查发现: 创新期望差距对领导创新投入产生U型影响; 领导创新投入中介创新期望差距与团队突破性创新之间的U型关系; 知觉资质过剩和组织晋升标准共同调节创新期望差距通过领导创新投入对团队突破性创新的影响, 具体地, 当领导知觉资质过剩高且组织实行相对晋升标准时, 创新期望差距通过领导创新投入对团队突破性创新施加更强影响。     

Rank disagreement: A comparison of multi-criteria methodologies

A number of multi-criteria decision support techniques have emerged in recent years that use varying computational approaches to arrive at the most desirable solution and thereby ‘recommend’ a course of action. Decision makers who use the results of this analytic work should be assured that the computational schemes used by their supporting analysts or decision support software produce the appropriate solutions. We conducted a series of simulation experiments that compared the top-ranked options resulting from the computational algorithms that support Multi-Attribute Value Theory (MAVT) and three methods that are reported in the literature that allow rank reversals, the change in rank order of two options when an unrelated option is added or deleted from the analysis: the Analytical Hierarchy Process (AHP), Percentaging and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We also included a Fuzzy algorithm proposed by Yager to gauge its consistency with the other algorithms, even though it is not subject to rank reversals. These experiments demonstrated that the MAVT and AHP techniques, when provided with the same decision outcome data, very often identify the same alternative as ‘best’. The other techniques are noticeably less consistent with MAVT, the Fuzzy algorithm being the least consistent. The situations under which the most frequent and significant differences occurred were dependent upon the method. The results of our experiments indicate that other issues (e.g. the processes used for problem structuring and the elicitation of value weights) are likely to be of greater significance to problem outcome (based on our experience) than the choice between the computational algorithms of MAVT and AHP. The results cause us to be concerned about the use of the other methods.     

The assistant referees’ activity in refereeing elite football: Preoccupations when not judging offside

ObjectiveThe purpose of this research was to study the preoccupations assistant referees had to participate in decision making about duels during football games.DesignResearch adopted a phenomenological framework to investigate the assistant referees’ lived experiences in order to understand their activity when they judged duels in match.MethodThis study investigated six professional football matches. Researchers conducted a participatory observation of the refereeing team before each match. Twelve self-confrontation interviews with each assistant referee of each match were conducted in order to make him/her describing his/her unfolding lived experience during the match.ResultsIn case of players’ duels, the perception of contextual cues enabled the assistants to appraise the occurring of a decision process with the central referee. For the assistants, the occurring of a decision process with the central referee meant his priority to intervene in the adjudication of duels, while the absence of decision process with the central referee meant for the assistants the possibility to intervene. The assistants adjusted their way of judging duels to how the central referee judged the previous ones.ConclusionsThe participation of assistants in decision making about duels depends on their preoccupations concerning the central referee’s priority. The way assistants perceive the central referee’s contextual judgment shapes the way they adjudicate duels. A latent intention to coordinate with the central referee, in relation with their collaborative tasks, is embedded in their preoccupations. Our results are a platform to develop further research about the referees’ collective activity.     

A one-boundary drift-diffusion model for time to collision estimation in a simple driving task

ABSTRACT

Driving is a complex everyday task. Every year a huge number of driving accidents around the world causes serious physical and mental injuries and deaths. The correct estimation of the remaining time to reach the other vehicles on the road, known as time to collision (TTC), is an important factor to avoid accidents. In this study, we aimed to use a drift-diffusion model (DDM) to better understand the participants’ estimation of TTC in two driving experiments. Both experiments were the same, except that in one of them participants were asked to finish the experiment as fast as they could, while in the other experiment there was no time constraint. DDM fitted the data from all participants well in both experiments according to the chi-square goodness of fit criterion. Also, results showed that time pressure increases subjects’ estimated TTC, the rate of accumulation of sensory information and the response threshold.     

Decision by sampling

We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute's subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision's context and also the background, real-world distribution of attribute values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities.     

Rotation in the dynamic factor modeling of multivariate stationary time series

A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of aq-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average. This is accomplished by minimizing a so-called state-space criterion that penalizes deviations of the rotated solution from a generalized state-space model with only instantaneous factor loadings. Alternative criteria are discussed in the closing section. The results of an empirical application are presented in some detail.This research was supported by the Institute for Developmental and Health Research Methodology, University of Virginia.     

The propensity theory: a decision-theoretic restatement

Probability theory is important because of its relevance for decision making, which also means: its relevance for the single case. The propensity theory of objective probability, which addresses the single case, is subject to two problems: Humphreys’ problem of inverse probabilities and the problem of the reference class. The paper solves both problems by restating the propensity theory using (an objectivist version of) Pearl’s approach to causality and probability, and by applying a decision-theoretic perspective. Contrary to a widely held view, decision making on the basis of given propensities can proceed without a subjective-probability supplement to propensities.