Empirical Bayes Derivative Estimates

Abstract

A dynamic system is a set of interacting elements characterized by changes occurring over time. The estimation of derivatives is a mainstay for exploring dynamics of constructs, particularly when the dynamics are complicated or unknown. The presence of measurement error in many social science constructs frequently results in poor estimates of derivatives, as even modest proportions of measurement error can compound when estimating derivatives. Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent growth curve models and mixed models under some conditions, derivatives could be estimated from estimates of random effects. This article proposes a new method for estimating derivatives based on calculating the Empirical Bayes estimates of derivatives from a mixed model. Two simulations compare four derivative estimation methods: Generalized Local Linear Approximation, Generalized Orthogonal Derivative Estimates, Functional Data Analysis, and the proposed Empirical Bayes Derivative Estimates. The simulations consider two data collection scenarios: short time series (≤10 observations) from many individuals or occasions, and long individual time series (25–500 observations). A substantive example visualizing the dynamics of intraindividual positive affect time series is also presented.     

Initial validation of the trust of automated systems test (TOAST)

ABSTRACT

Trust is a key determinant of whether people rely on automated systems in the military and the public. However, there is currently no standard for measuring trust in automated systems. In the present studies, we propose a scale to measure trust in automated systems that is grounded in current research and theory on trust formation, which we refer to as the Trust in Automated Systems Test (TOAST). We evaluated both the reliability of the scale structure and criterion validity using independent, military-affiliated and civilian samples. In both studies we found that the TOAST exhibited a two-factor structure, measuring system understanding and performance (respectively), and that factor scores significantly predicted scores on theoretically related constructs demonstrating clear criterion validity. We discuss the implications of our findings for advancing the empirical literature and in improving interface design.     

Water use scenarios assessment using multicriteria analysis

Water management is a fertile terrain for research, and can be investigated using several methodological instruments and approaches. Multipurpose water resources, which allow for the contemporary presence of in‐stream (fishing, swimming, etc.) and off‐stream uses (agriculture, household, etc.), are particularly difficult to management due to increasing water demand and the conflict between consumptive and not consumptive uses. New scenarios in agricultural policy (Reform of the European Common Agricultural Policy) and new requests from local stakeholders (recreational activities, rising household water demand, etc.) involve use of decision support methods to find a balance between multiple potential uses. This study describes the application of multicriteria decision aid for choosing the best project for water management and local development among a set of alternatives, using the regime method. The regime method can integrate quantitative data with quality judgement and preference index. The study aims to verify if the regime approach is understandable for the decision maker and if it is suitable for use in ambiguous situations where no quantitative information is available. It is not always possible to get the ‘best alternative’ in multicriteria evaluation: in this study we found two top‐rank alternatives, with minor differences, to submit to the decision maker. Copyright © 2011 John Wiley & Sons, Ltd.     

Lexical and sublexical cortical tuning for print revealed by Steady-State Visual Evoked Potentials (SSVEPs) in early readers

There are multiple levels of processing relevant to reading that vary in their visual, sublexical, and lexical orthographic processing demands. Segregating distinct cortical sources for each of these levels has been challenging in EEG studies of early readers. To address this challenge, we applied recent advances in analyzing high-density EEG using Steady-State Visual Evoked Potentials (SSVEPs) via data-driven Reliable Components Analysis (RCA) in a group of early readers spanning from kindergarten to second grade. Three controlled stimulus contrasts—familiar words versus unfamiliar pseudofonts, familiar words versus pseudowords, and pseudowords versus nonwords—were used to isolate coarse print tuning, lexical processing, and sublexical orthography-related processing, respectively. First, three overlapping yet distinct neural sources—left vOT, dorsal parietal, and primary visual cortex were revealed underlying coarse print tuning. Second, we segregated distinct cortical sources for the other two levels of processing: lexical fine tuning over occipito-temporal/parietal regions; sublexical orthographic fine tuning over left occipital regions. Finally, exploratory group analyses based on children's reading fluency suggested that coarse print tuning emerges early even in children with limited reading knowledge, while sublexical and higher-level lexical processing emerge only in children with sufficient reading knowledge.

Research Highlights

• Cognitive processes underlying coarse print tuning, sublexical, and lexical fine tuning were examined in beginning readers.
• Three overlapping yet distinct neural sources—left ventral occipito-temporal (vOT), left temporo-parietal, and primary visual cortex—were revealed underlying coarse print tuning.
• Responses to sublexical orthographic fine tuning were found over left occipital regions, while responses to higher-level linguistic fine tuning were found over occipito-temporal/parietal regions.
• Exploratory group analyses suggested that coarse print tuning emerges in children with limited reading knowledge, while sublexical and higher-level linguistic fine tuning effects emerge in children with sufficient reading knowledge.