Intentional response distortion during the COVID-19 pandemic

COVID-19 has abruptly and unexpectedly transformed nearly every aspect of work, including but not limited to increased unemployment rates and uncertainty regarding future job prospects. Response distortion has always been a concern given that many organizations rely on information that is self-reported by applicants regarding their potential employability (e.g., responses to self-reported personality instruments, resumes, interview responses). Drawing from the Valence-Instrumentality-Expectancy (VIE) theory of motivation, we propose that the uncertainty surrounding jobs may lead to amplified distorted responses on these measures in areas where COVID-19 was most salient. In a sample of 213 working adults [~50% female, age M = 38.48], the present study shows that increases in response distortion on a measure of conscientiousness were more pronounced as a function of (a) local COVID positivity rates and (b) job type, such that frontline workers distorted their responses the most. Findings are discussed in the context of VIE theory, personality measurement, and challenges with maintaining effective selection procedures.     

Extending exploratory diagnostic classification models: Inferring the effect of covariates

Diagnostic models provide a statistical framework for designing formative assessments by classifying student knowledge profiles according to a collection of fine-grained attributes. The context and ecosystem in which students learn may play an important role in skill mastery, and it is therefore important to develop methods for incorporating student covariates into diagnostic models. Including covariates may provide researchers and practitioners with the ability to evaluate novel interventions or understand the role of background knowledge in attribute mastery. Existing research is designed to include covariates in confirmatory diagnostic models, which are also known as restricted latent class models. We propose new methods for including covariates in exploratory RLCMs that jointly infer the latent structure and evaluate the role of covariates on performance and skill mastery. We present a novel Bayesian formulation and report a Markov chain Monte Carlo algorithm using a Metropolis-within-Gibbs algorithm for approximating the model parameter posterior distribution. We report Monte Carlo simulation evidence regarding the accuracy of our new methods and present results from an application that examines the role of student background knowledge on the mastery of a probability data set.     

Adaptation, teleology, and selection by consequences

This paper presents and defends the view that reinforcement and natural selection are selection processes, that selection processes are neither mechanistic nor teleological, and that mentalistic and vitalistic processes are teleological but not mechanistic. The differences between these types of processes are described and used in discussing the conceptual and methodological significance of “selection type theories” and B. F. Skinner's radical behaviorist view that “operant behavior is the field of intention, purpose, and expectation. It deals with that field precisely as the theory of evolution has dealt with another kind of purpose” (1986, p. 716). The antimentalism of radical behaviorism emerges as a post-Darwinian extension of Francis Bacon's (and Galileo's) influential view that “[the introduction of final causes] rather corrupts than advances the sciences” (Bacon, 1905, p. 302).     

Analyzing sequential categorical data: Individual variation in markov chains

Markov chains are probabilistic models for sequences of categorical events, with applications throughout scientific psychology. This paper provides a method for anlayzing data consisting of event sequences and covariate observations. It is assumed that each sequence is a Markov process characterized by a distinct transition probability matrix. The objective is to use the covariate data to explain differences between individuals in the transition probability matrices characterizing their sequential data. The elements of the transition probability matrices are written as functions of a vector of latent variables, with variation in the latent variables explained through a multivariate regression on the covariates. The regression is estimated using the EM algorithm, and requires the numerical calculation of a multivariate integral. An example using simulated cognitive developmental data is presented, which shows that the estimation of individual variation in the parameters of a probability model may have substantial theoretical importance, even when individual differences are not the focus of the investigator's concerns.Research contributing to this article was supported by B.R.S. Subgrant 5-35345 from the University of Virginia. I thank the DADA Group, Bill Fabricius, Don Hartmann, William Griffin, Jack McArdle, Ivo Molenaar, Ronald Schoenberg, Simon Tavaré, and several anonymous reviewers for their discussion of these points.     

A general solution of the weighted orthonormal procrustes problem

A general solution for weighted orthonormal Procrustes problem is offered in terms of the least squares criterion. For the two-demensional case. this solution always gives the global minimum; for the general case, an algorithm is proposed that must converge, although not necessarily to the global minimum. In general, the algorithm yields a solution for the problem of how to fit one matrix to another under the condition that the dimensions of the latter matrix first are allowed to be transformed orthonormally and then weighted differentially, which is the task encountered in fitting analogues of the IDIOSCAL and INDSCAL models to a set of configurations.The authors are grateful to the Editor and the anonymous reviewers for their helpful comments on an earlier draft of this paper.     

Modeling item responses when different subjects employ different solution strategies

A model is presented for item responses when different subjects employ different strategies, but only responses, not choice of strategy, can be observed. Using substantive theory to differentiate the likelihoods of response vectors under a fixed set of strategies, we model response probabilities in terms of item parameters for each strategy, proportions of subjects employing each strategy, and distributions of subject proficiency within strategies. The probabilities that an individual subject employed the various strategies can then be obtained, along with a conditional estimate of proficiency under each. A conceptual example discusses response strategies for spatial rotation tasks, and a numerican example resolves a population of subjects into subpopulations of valid responders and random guessers.The first author's work was supported by Contract No. N00014-85-K-0683, project designation NR 150-539, from the Cognitive Science Program, Cognitive and Neural Sciences Division, Office of Naval Research. We are grateful to Murray Aitkin, Isaac Bejar, Neil Dorans, Frederiksen, and Marklyn Wingersky for their comments and suggestions, and to Alison Gooding, Maxine Kingston, Donna Lembeck, Joling Liang, and Kentaro Yamamoto for their assistance with Example 2.     

四卡问题的内容促进效应的实验研究

本研究设计了２种抽象材料和４种具体材料的四卡问题,对４３６名大学生进行测试,以考察被试解决四卡问题时所采用的思维方式并检验命题内容对推理的影响。结果表明,四卡问题十分困难,具体内容的四卡问题并不能产生促进效应,大学生的推理表现出“匹配偏向”的特点。     

EVOLUTION IN THERMODYNAMIC PERSPECTIVE: A HISTORICAL AND PHILOSOPHICAL ANGLE

Abstract. The recently suggested reformulation of Darwinian evolutionary theory, based on the thermodynamics of self-organizing processes, has strong philosophical implications. My claim is that the main philosophical merit of the thermodynamic approach, made especially clear in J.S. Wicken's work, is its insistence on the law-governed, continuous nature of evolution. I attempt to substantiate this claim following a historical analysis of beginning-of-the-century ideas on evolution and matter-life relationship, in particular, the fitness-of-the-environment-for-life theory of the Harvard physiologist L.J. Henderson. In addition, I point to an epistemological common ground underlying the studies of the “thermodynamics school” and other currently active research groups focusing on the emergence and evolution of biological organization.     

A general linear model for estimating effect size in the presence of publication bias

When the process of publication favors studies with smallp-values, and hence large effect estimates, combined estimates from many studies may be biased. This paper describes a model for estimation of effect size when there is selection based on one-tailedp-values. The model employs the method of maximum likelihood in the context of a mixed (fixed and random) effects general linear model for effect sizes. It offers a test for the presence of publication bias, and corrected estimates of the parameters of the linear model for effect magnitude. The model is illustrated using a well-known data set on the benefits of psychotherapy.Authors' note: The contributions of the authors are considered equal, and the order of authorship was chosen to be reverse-alphabetical.     

Identification of inconsistent variates in factor analysis

When some of observed variates do not conform to the model under consideration, they will have a serious effect on the results of statistical analysis. In factor analysis the model with inconsistent variates may result in improper solutions. In this article a useful method for identifying a variate as inconsistent is proposed in factor analysis. The procedure is based on the likelihood principle. Several statistical properties such as the effect of misspecified hypotheses, the problem of multiple comparisons, and robustness to violation of distributional assumptions are investigated. The procedure is illustrated by some examples.