Direct parameter estimation for generalised balanced power diagrams

The statistical characterisation and synthetic reproduction of a polycrystalline material's microstructure is assisted by mathematically representing its morphology by a tessellation model. The generalised balanced power diagram (GBPD) is a tessellation model that was shown in previous studies to accurately reproduce the microstructure morphology of various materials by closely matching micrographs obtained through electron microscopy. These studies employed costly optimisation procedures to determine the best-fit model parameters, limiting the scalability of the model. In this work, it is shown that setting the tessellation cell parameters to values such that the shape moments of the corresponding grains are matched results in a quality of fit that is commensurate with optimisation procedures. This fitting approach decouples the interaction among grains when fitting the tessellation parameters and, most notably, provides analytical, closed-form expressions for all the model parameters. The performance of this parameter fitting approach is demonstrated on multiple micrographs of various materials, and it compares similarly to the performance of optimisation procedures reported in recently published literature. As the fitted parameter values are obtained through trivial computations, this approach enables extensive scalability of the GBPD model such that it can be used to represent extremely large characterisation data sets.     

Color Selectivity of the Spatial Congruency Effect: Evidence from the Focused Attention Paradigm

The multisensory response enhancement (MRE), occurring when the response to a visual target integrated with a spatially congruent sound is stronger than the response to the visual target alone, is believed to be mediated by the superior colliculus (SC) (Stein & Meredith, 1993). Here, we used a focused attention paradigm to show that the spatial congruency effect occurs with red (SC-effective) but not blue (SC-ineffective) visual stimuli, when presented with spatially congruent sounds. To isolate the chromatic component of SC-ineffective targets and to demonstrate the selectivity of the spatial congruency effect we used the random luminance modulation technique (Experiment 1) and the tritanopic technique (Experiment 2). Our results indicate that the spatial congruency effect does not require the distribution of attention over different sensory modalities and provide correlational evidence that the SC mediates the effect.     

Empirical underidentification in estimating random utility models: The role of choice sets and standardizations

A standard approach to distinguishing people’s risk preferences is to estimate a random utility model using a power utility function to characterize the preferences and a logit function to capture choice consistency. We demonstrate that with often-used choice situations, this model suffers from empirical underidentification, meaning that parameters cannot be estimated precisely. With simulations of estimation accuracy and Kullback–Leibler divergence measures we examined factors that potentially mitigate this problem. First, using a choice set that guarantees a switch in the utility order between two risky gambles in the range of plausible values leads to higher estimation accuracy than randomly created choice sets or the purpose-built choice sets common in the literature. Second, parameter estimates are regularly correlated, which contributes to empirical underidentification. Examining standardizations of the utility scale, we show that they mitigate this correlation and additionally improve the estimation accuracy for choice consistency. Yet, they can have detrimental effects on the estimation accuracy of risk preference. Finally, we also show how repeated versus distinct choice sets and an increase in observations affect estimation accuracy. Together, these results should help researchers make informed design choices to estimate parameters in the random utility model more precisely.     

A Test of the Adams-Creamer Decay Hypothesis for the Timing of Motor Responses

The Adams-Creamer hypothesis states that S uses the decay of proprioceptive feedback from an early portion of a movement to cue a timed response at some later time. This hypothesis was tested by creating passive left-arm movement in one group and withholding it from another, and having Ss make a right-hand response when exactly 2.0 sec. had elapsed since the end of the movement Ss with left-arm feedback had less absolute and algebraic error, and greater within-S consistency than did the no-movement control Ss and, when KR was withdrawn, Ss with left-arm movement regressed less than did Ss without the left-arm movement, which provided 2 lines of support for the decay hypothesis.     

Heterogeneous factor analysis models: A bayesian approach

Multilevel factor analysis models are widely used in the social sciences to account for heterogeneity in mean structures. In this paper we extend previous work on multilevel models to account for general forms of heterogeneity in confirmatory factor analysis models. We specify various models of mean and covariance heterogeneity in confirmatory factor analysis and develop Markov Chain Monte Carlo (MCMC) procedures to perform Bayesian inference, model checking, and model comparison.We test our methodology using synthetic data and data from a consumption emotion study. The results from synthetic data show that our Bayesian model perform well in recovering the true parameters and selecting the appropriate model. More importantly, the results clearly illustrate the consequences of ignoring heterogeneity. Specifically, we find that ignoring heterogeneity can lead to sign reversals of the factor covariances, inflation of factor variances and underappreciation of uncertainty in parameter estimates. The results from the emotion study show that subjects vary both in means and covariances. Thus traditional psychometric methods cannot fully capture the heterogeneity in our data.     

Is the “hot‐hands” phenomenon a misperception of random events?

T. Gilovich, R. Vallone, and A. Tversky (1985) asked whether the so-called hot-hands phenomenon – a temporary elevation of the probability of successful shots – actually exists in basketball. They concluded that hot-hands are misperceived random events. This paper re-examines the truth of their conclusion. The present study's main concern was the sensitivity of the statistical tests used in Gilovich et al.'s research. Simulated records of shots over a season were used. These represented many different situations and players, but they always contained at least one hot-hand period. The issue was whether Gilovich et al.'s tests were sensitive enough to detect the hot-hands embedded in the records. The study found that this sensitivity depends on the frequency of hot-hand periods, the total number of shots in all hot-hand periods, the number of shots in each hot-hand period, and the size of the increase in the probability of successful shots in hot-hand periods. However, when the values of those variables were set realistically, on average the tests could detect only about 12% of the hot-hands phenomena.     

Variability and Determinism in Motor Behavior

In investigations into perception-action systems, variability of observable behavior may be considered to (a) interfere with inquiry, (b) be neither detrimental nor particularly useful to inquiry, or (c) play a crucial role in inquiry. The authors underscore recent suggestions that alternative (c) is a preferred strategy for the study of many motor behaviors. In tutorial fashion, the authors review the concepts of variability and determinism with respect to postural and rhythmic movements. Study of the variability of those behaviors has revealed crucial features suggestive of underlying mechanisms and control, such as particular blends of noise and determinism (piecewise determinism). It has also revealed general lessons (for example, more variable does not mean more random and more controllable does not mean more deterministic) that may extend to other classes of perceptual-motor behavior.     

Evaluating the Impact of Careless Responding on Aggregated-Scores: To Filter Unmotivated Examinees or Not?

When examinees' test-taking motivation is questionable, practitioners must determine whether careless responding is of practical concern and if so, decide on the best approach to filter such responses. As there has been insufficient research on these topics, the objectives of this study were to: a) evaluate the degree of underestimation in the true mean when careless responses are present, and b) compare the effectiveness of two filtering procedures in purifying biased aggregated-scores. Results demonstrated that: a) the true mean was underestimated by around 0.20 SDs if the total amount of careless responses exceeded 6.25%, 12.5%, and 12.5% for easy, moderately difficult, and difficult tests, respectively, and b) listwise deleting data from unmotivated examinees artificially inflated the true mean by as much as .42 SDs when ability was related to careless responding. Findings from this study have implications for when and how practitioners should handle careless responses for group-based low-stakes assessments.     

Non‐ignorable missingness item response theory models for choice effects in examinee‐selected items

Examinee‐selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non‐ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two‐dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non‐ignorable and to determine how to apply the new model to the data collected. Two follow‐up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non‐ignorable missing data were mistakenly treated as ignorable.