Kensuke Okada

Comprehensive Comparison of Self-administered Questionnaires for Measuring Quantitative Autistic Traits in Adults

We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype Questionnaire, the Social Responsiveness Scale2-Adult Self report (SRS2-AS), and the Autism-Spectrum Quotient (AQ). The SRS2-AS and the AQ each had several short forms that we also examined, bringing the total to 11 forms. Though all QAT questionnaires showed acceptable levels of test–retest reliability, the AQ and SRS2-AS, including their short forms, exhibited poor internal consistency and discriminant validity, respectively. The SATQ excelled in terms of classical test theory and due to its short length.

Neural correlate of human reciprocity in social interactions

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoners dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions.

Developmental Trajectories of Social Skills during Early Childhood and Links to Parenting Practices in a Japanese Sample

This study used data from a nationwide survey in Japan to model the developmental course of social skills during early childhood. The goals of this study were to identify longitudinal profiles of social skills between 2 and 5 years of age using a group-based trajectory approach, and to investigate whether and to what extent parenting practices at 2 years of age predicted developmental trajectories of social skills during the preschool period. A relatively large sample of boys and girls (N > 1,000) was assessed on three social skill dimensions (Cooperation, Self-control, and Assertion) at four time points (ages 2, 3, 4, and 5), and on four parenting practices (cognitive and emotional involvement, avoidance of restriction and punishment, social stimulation, and social support for parenting) at age 2. The results indicated that for each social skill dimension, group-based trajectory models identified three distinct trajectories: low, moderate, and high. Multinomial regression analysis revealed that parenting practice variables showed differential contributions to development of child social skills. Specifically, Cooperation and Assertion were promoted by cognitive and emotional involvement, Self-control by social stimulation, and Assertion by avoidance of restriction and punishment. Abundant social support for parenting was not associated with higher child social skills trajectories. We found heterogeneity in developmental profiles of social skills during the preschool ages, and we identified parenting practices that contributed to different patterns of social skills development. We discussed the implications of higher-quality parenting practices on the improvement of child social skills across early childhood.

Bayesian multidimensional scaling for the estimation of a Minkowski exponent

The Minkowski property of psychological space has long been of interest to researchers. A common strategy has been calculating the stress in multidimensional scaling for many Minkowski exponent values and choosing the one that results in the lowest stress. However, this strategy has an arbitrariness problem—that is, a loss function. Although a recently proposed Bayesian approach could solve this problem, the method was intended for individual subject data. It is unknown whether this method is directly applicable to averaged or single data, which are common in psychology and behavioral science. Therefore, we first conducted a simulation study to evaluate the applicability of the method to the averaged data problem and found that it failed to recover the true Minkowski exponent. Therefore, a new method is proposed that is a simple extension of the existing Euclidean Bayesian multidimensional scaling to the Minkowski metric. Another simulation study revealed that the proposed method could successfully recover the true Minkowski exponent. BUGS codes used in this study are given in the Appendix.

Simplification and Shift in Cognition of Political Difference: Applying the Geometric Modeling to the Analysis of Semantic Similarity Judgment

Perceiving differences by means of spatial analogies is intrinsic to human cognition. Multi-dimensional scaling (MDS) analysis based on Minkowski geometry has been used primarily on data on sensory similarity judgments, leaving judgments on abstractive differences unanalyzed. Indeed, analysts have failed to find appropriate experimental or real-life data in this regard. Our MDS analysis used survey data on political scientists judgments of the similarities and differences between political positions expressed in terms of distance. Both distance smoothing and majorization techniques were applied to a three-way dataset of similarity judgments provided by at least seven experts on at least five parties positions on at least seven policies (i.e., originally yielding 245 dimensions) to substantially reduce the risk of local minima. The analysis found two dimensions, which were sufficient for mapping differences, and fit the city-block dimensions better than the Euclidean metric in all datasets obtained from 13 countries. Most city-block dimensions were highly correlated with the simplified criterion (i.e., the left–right ideology) for differences that are actually used in real politics. The isometry of the city-block and dominance metrics in two-dimensional space carries further implications. More specifically, individuals may pay attention to two dimensions (if represented in the city-block metric) or focus on a single dimension (if represented in the dominance metric) when judging differences between the same objects. Switching between metrics may be expected to occur during cognitive processing as frequently as the apparent discontinuities and shifts in human attention that may underlie changing judgments in real situations occur. Consequently, the result has extended strong support for the validity of the geometric models to represent an important social cognition, i.e., the one of political differences, which is deeply rooted in human nature.

Comparison among cognitive diagnostic models for the TIMSS 2007 fourth grade mathematics assessment

A variety of cognitive diagnostic models (CDMs) have been developed in recent years to help with the diagnostic assessment and evaluation of students. Each model makes different assumptions about the relationship between students’ achievement and skills, which makes it important to empirically investigate which CDMs better fit the actual data. In this study, we examined this question by comparatively fitting representative CDMs to the Trends in International Mathematics and Science Study (TIMSS) 2007 assessment data across seven countries. The following two major findings emerged. First, in accordance with former studies, CDMs had a better fit than did the item response theory models. Second, main effects models generally had a better fit than other parsimonious or the saturated models. Related to the second finding, the fit of the traditional parsimonious models such as the DINA and DINO models were not optimal. The empirical educational implications of these findings are discussed.

Bayesian meta-analysis of Cronbach's coefficient alpha to evaluate informative hypotheses

This paper proposes a new method to evaluate informative hypotheses for meta-analysis of Cronbachs coefficient alpha using a Bayesian approach. The coefficient alpha is one of the most widely used reliability indices. In meta-analyses of reliability, researchers typically form specific informative hypotheses beforehand, such as alpha of this test is greater than 0.8 or alpha of one form of a test is greater than the others. The proposed method enables direct evaluation of these informative hypotheses. To this end, a Bayes factor is calculated to evaluate the informative hypothesis against its complement. It allows researchers to summarize the evidence provided by previous studies in favor of their informative hypothesis. The proposed approach can be seen as a natural extension of the Bayesian meta-analysis of coefficient alpha recently proposed in this journal (Brannick and Zhang, 2013). The proposed method is illustrated through two meta-analyses of real data that evaluate different kinds of informative hypotheses on superpopulation: one is that alpha of a particular test is above the criterion value, and the other is that alphas among different test versions have ordered relationships. Informative hypotheses are supported from the data in both cases, suggesting that the proposed approach is promising for application.

Modeling When People Quit: Bayesian Censored Geometric Models with Hierarchical and Latent-Mixture Extensions

People often interact with environments that can provide only a finite number of items as resources. Eventually a book contains no more chapters, there are no more albums available from a band, and every Pokémon has been caught. When interacting with these sorts of environments, people either actively choose to quit collecting new items, or they are forced to quit when the items are exhausted. Modeling the distribution of how many items people collect before they quit involves untangling these two possibilities, We propose that censored geometric models are a useful basic technique for modeling the quitting distribution, and, show how, by implementing these models in a hierarchical and latent-mixture framework through Bayesian methods, they can be extended to capture the additional features of specific situations. We demonstrate this approach by developing and testing a series of models in two case studies involving real-world data. One case study deals with people choosing jokes from a recommender system, and the other deals with people completing items in a personality survey.

Researchers’ choice of the number and range of levels in experiments affects the resultant variance-accounted-for effect size

In psychology, the reporting of variance-accounted-for effect size indices has been recommended and widely accepted through the movement away from null hypothesis significance testing. However, most researchers have paid insufficient attention to the fact that effect sizes depend on the choice of the number of levels and their ranges in experiments. Moreover, the functional form of how and how much this choice affects the resultant effect size has not thus far been studied. We show that the relationship between the population effect size and number and range of levels is given as an explicit function under reasonable assumptions. Counterintuitively, it is found that researchers may affect the resultant effect size to be either double or half simply by suitably choosing the number of levels and their ranges. Through a simulation study, we confirm that this relation also applies to sample effect size indices in much the same way. Therefore, the variance-accounted-for effect size would be substantially affected by the basic research design such as the number of levels. Simple cross-study comparisons and a meta-analysis of variance-accounted-for effect sizes would generally be irrational unless differences in research designs are explicitly considered.

Negative estimate of variance-accounted-for effect size: How often it is obtained, and what happens if it is treated as zero.

Researchers recommend reporting ofxa0bias-corrected variance-accounted-for effect size estimates such as omega squared instead of uncorrected estimates, because the latter are known for their tendency toward overestimation, whereas the former mostly correct this bias. However, this argument may miss an important fact: A bias-corrected estimate can take a negative value, and of course, a negative variance ratio does not make sense. Therefore, it has been a common practice to report an obtained negative estimate as zero. This article presents an argument against this practice, based on a simulation study investigating how often negative estimates are obtained and what are the consequences of treating them as zero. The results indicate that negative estimates are obtained more often than researchers might have thought. In fact, they occur more than half the time under some reasonable conditions. Moreover, treating the obtained negative estimates as zero causes substantial overestimation of even bias-corrected estimators when the sample size and population effect are not large, which is often the case in psychology. Therefore, the recommendation is that researchers report obtained negative estimates as is, instead of reporting them as zero, to avoid the inflation of effect sizes in research syntheses, even though zero can be considered the most plausible value when interpreting such a result. R code to reproduce all of the described results is included as supplemental material.