Human risky choice under temporal constraints: tests of an energy-budget model

Risk-sensitive foraging models predict that choice between fixed and variable food delays should be influenced by an organism's energy budget. To investigate whether the predictions of these models could be extended to choice in humans, risk sensitivity in 4 adults was investigated under laboratory conditions designed to model positive and negative energy budgets. Subjects chose between fixed and variable trial durations with the same mean value. An energy requirement was modeled by requiring that five trials be completed within a limited time period for points delivered at the end of the period (block of trials) to be exchanged later for money. Manipulating the duration of this time period generated positive and negative earnings budgets (or, alternatively, "time budgets"). Choices were consistent with the predictions of energy-budget models: The fixed-delay option was strongly preferred under positive earnings-budget conditions and the variable-delay option was strongly preferred under negative earnings-budget conditions. Within-block (or trial-by-trial) choices were also frequently consistent with the predictions of a dynamic optimization model, indicating that choice was simultaneously sensitive to the temporal requirements, delays associated with fixed and variable choices on the upcoming trial, cumulative delays within the block of trials, and trial position within a block.     

How Can Contextual Variables Influence Creative Thinking? Contributions from the Optimal-Level of Arousal Model

More and more research is showing how different environments can lead to greater or lower creative skills. The purpose of this concept paper is to introduce a novel application of the optimal-level of arousal model that could address inconsistencies present in the literature. After introducing possible definitions of creativity, I discuss the optimal-level of arousal theory and how considering the “arousal” and “mood changing” potentials of contexts could enlighten findings related to inter-individual differences, domain-specificities, developmental aspects, and gender differences. Among other things, this model will clarify the factors influencing motivation to display creative skills which could improve the external validity of creativity studies. Examples of the kinds of hypotheses that can be tested by applying this model in future creative studies will also be proposed.     

A distance-based variety of nonlinear multivariate data analysis, including weights for objects and variables

In the distance approach to nonlinear multivariate data analysis the focus is on the optimal representation of the relationships between the objects in the analysis. In this paper two methods are presented for including weights in distance-based nonlinear multivariate data analysis. In the first method, weights are assigned to the objects while the second method is concerned with differential weighting of groups of variables. When each analysis variable defines a group the latter method becomes a variable weighting method. For objects the weights are assumed to be given; for groups of variables they may be given, or estimated. These weighting schemes can also be combined and have several important applications. For example, they make it possible to perform efficient analyses of large data sets, to use the distance-based variety of nonlinear multivariate data analysis as an addition to loglinear analysis of multiway contingency tables, and to do stability studies of the solutions by applying the bootstrap on the objects or the variables in the analysis. These and other applications are discussed, and an efficient algorithm is proposed to minimize the corresponding loss function.This study is funded by The Netherlands Organization for Scientific Research (NWO) by grant nr. 030-56403 for the PIONEER project Subject Oriented Multivariate Analysis to the third author.     

Homogeneity analysis withk sets of variables: An alternating least squares method with optimal scaling features

Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple or single. The single transformations consist of three types: nominal, ordinal, and numerical. The corresponding OVERALS computer program minimizes a least squares loss function by using an alternating least squares algorithm. Many existing linear and nonlinear multivariate analysis techniques are shown to be special cases of OVERALS. An application to data from an epidemiological survey is presented.This research was partly supported by SWOV (Institute for Road Safety Research) in Leidschendam, The Netherlands.     

An examination of procedures for determining the number of clusters in a data set

A Monte Carlo evaluation of 30 procedures for determining the number of clusters was conducted on artificial data sets which contained either 2, 3, 4, or 5 distinct nonoverlapping clusters. To provide a variety of clustering solutions, the data sets were analyzed by four hierarchical clustering methods. External criterion measures indicated excellent recovery of the true cluster structure by the methods at the correct hierarchy level. Thus, the clustering present in the data was quite strong. The simulation results for the stopping rules revealed a wide range in their ability to determine the correct number of clusters in the data. Several procedures worked fairly well, whereas others performed rather poorly. Thus, the latter group of rules would appear to have little validity, particularly for data sets containing distinct clusters. Applied researchers are urged to select one or more of the better criteria. However, users are cautioned that the performance of some of the criteria may be data dependent.The authors would like to express their appreciation to a number of individuals who provided assistance during the conduct of this research. Those who deserve recognition include Roger Blashfield, John Crawford, John Gower, James Lingoes, Wansoo Rhee, F. James Rohlf, Warren Sarle, and Tom Soon.     

Alternative weights and invariant parameters in optimal scaling

Under conditions that are commonly satisfied in optimal scaling problems, arbitrary sets of optimal weights can be obtained by choices of generalized inverse procedures. A simple relationship holds between these and the corresponding invariant item scores. The case of optimal scaling originally treated by Guttman [1941] yields a restricted form of multicategory factor analysis. It is suggested that the invariant parameters of optimal scaling should be interpreted, according to the principles of latent trait theory, rather than the arbitrary weights.This paper benefits from a number of suggestions and comments made by Professors M. J. R. Healy, H. Goldstein, and S. Nishisato, and by Mr. C. Fraser, to whom grateful acknowledgments are due. The author is solely responsible for the final form of the paper, including of course such errors as may remain in it.This research was partly supported by Grant No. A6346 from the Natural Sciences and Engineering Research Council of Canada.     

项目难度与被试能力分布最优匹配的模拟研究

该文运用蒙特卡罗方法对被测试能力分布与测验项目难度分布的匹配问题进行模拟分析,分析表明当能力分布为正态分布正偏态分布和负偏态分布时分别与测验项目难度分布与为正态分布,正偏态分布和负偏态分布匹配,比别的匹配有更高测验期望信息值,测验最大信息测验 系数,并且测验信息曲线最大值的能力点与能力分布的众数愈相一致,测验项目参数估计值性真实值的相关也更高。     

The Conceptualization of Team Flow

Despite the noted potential for team flow to enhance a team's effectiveness, productivity, performance, and capabilities, studies on the construct in the workplace context are scarce. Most research on flow at the group level has been focused on performance in athletics or the arts, and looks at the collective experience. But, the context of work has different parameters, which necessitate a look at individual and team level experiences. In this review, we extend current theories and essay a testable, multilevel model of team flow in the workplace that includes its likely prerequisites, characteristics, and benefits.     

Minimax d-optimal designs for item response theory models

Various different item response theory (IRT) models can be used in educational and psychological measurement to analyze test data. One of the major drawbacks of these models is that efficient parameter estimation can only be achieved with very large data sets. Therefore, it is often worthwhile to search for designs of the test data that in some way will optimize the parameter estimates. The results from the statistical theory on optimal design can be applied for efficient estimation of the parameters.A major problem in finding an optimal design for IRT models is that the designs are only optimal for a given set of parameters, that is, they are locally optimal. Locally optimal designs can be constructed with a sequential design procedure. In this paper minimax designs are proposed for IRT models to overcome the problem of local optimality. Minimax designs are compared to sequentially constructed designs for the two parameter logistic model and the results show that minimax design can be nearly as efficient as sequentially constructed designs.     

Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection

Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended. If some of the abilities are nuisances, application of the criterion of A _s -optimality (or D _s -optimality), which focuses on the subset of intentional abilities is recommended. For the measurement of a linear combination of abilities, the criterion of c-optimality yielded the best results. The preferences of each of these criteria for items with specific patterns of parameter values was also assessed. It was found that the criteria differed mainly in their preferences of items with different patterns of values for their discrimination parameters. The first author is now at the Department of Methodology and Statistics, Statistics, Faculty of Social Sciences, Utrecht University, Heidelberglaan 1, 3854 Utrecht, The Netherlands. The second author is now at Research Department, CTB/McGraw-Hill, Monterey, CA, USA.