Children's interpretation of adult nonreaction: A trial-by-trial self-report assessment and evidence for contrast effects in an observational context

The study investigated children's interpretation of blank reaction (nonreaction) from one adult to another as a function of its pairing with positive or negative overt feedback. Each child watched through a one-way mirror as an evaluating adult provided feedback to a second adult who was performing on a two-choice discrimination task. After six initial blank reaction trials, children observed one of four types of feedback combinations over 60 experimental trials: (a) right feedback on some trials and blank reactions on others, (b) wrong feedback on some trials and blank reactions on others, (c) right, wrong, and nonreaction on different trials, or (d) nonreaction on all trials. There was little evidence that children consistently interpreted blank reaction as meaning right independent of feedback combination. In contrast, in the Right-Blank and Wrong-Blank feedback combinations, children interpreted blank as meaning the opposite of the overt feedback it was paired with on over two-thirds of the trials, with no sex differences or test anxiety effects.     

The Application of Constraint Semantics to the Language of Subjective Uncertainty

This paper develops a compositional, type-driven constraint semantic theory for a fragment of the language of subjective uncertainty. In the particular application explored here, the interpretation function of constraint semantics yields not propositions but constraints on credal states as the semantic values of declarative sentences. Constraints are richer than propositions in that constraints can straightforwardly represent assessments of the probability that the world is one way rather than another. The richness of constraints helps us model communicative acts in essentially the same way that we model agents’ credences. Moreover, supplementing familiar truth-conditional theories of epistemic modals with constraint semantics helps capture contrasts between strong necessity and possibility modals, on the one hand, and weak necessity modals, on the other.     

Bayesian Factor Analysis as a Variable-Selection Problem: Alternative Priors and Consequences

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor-loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, Muthén & Asparouhov proposed a Bayesian structural equation modeling (BSEM) approach to explore the presence of cross loadings in CFA models. We show that the issue of determining factor-loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov's approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike-and-slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set is used to demonstrate our approach.