Optimality And Concurrent Variable-interval Variable-ratio Schedules

Despite claims to the contrary, all leading theories about operant choice may be seen as models of optimality. Although melioration is often contrasted with global maximization, both make the same core assumptions as other versions of optimality theory, including momentary maximizing, hill climbing, and the various versions of optimal foraging theory. The present experiment aimed to test melioration against more global optimality and to apply the visit-by-visit analysis suggested by foraging theory. Rats were exposed to concurrent schedules in which one alternative was always variable-ratio 10 and the other alternative was a variable-interval schedule. Although choice relations varied from rat to rat, the overall results roughly confirmed the matching law, a result often taken to support melioration. Pooling the data across sessions and across rats, however, resulted in no increment in unsystematic variance, lending support to the contention by Ziriax and Silberberg (1984) that the choice relation is partly constrained. When the data were analyzed at the level of visits, the results either disconfirmed predictions of melioration or showed regularities about which melioration is silent. Instead, performance tended toward a rough optimization, in which responding favored the variable ratio, but with relatively brief visits to the variable interval. There were no asymmetries in travel or variability that would indicate that different processes were involved in generating visits at the two different schedules. The findings point toward a more global optimality model than melioration and demonstrate the value of per-visit analysis in the study of concurrent performances.     

Some critical observations of the test information function as a measure of local accuracy in ability estimation

The test information function serves important roles in latent trait models and in their applications. Among others, it has been used as the measure of accuracy in ability estimation. A question arises, however, if the test information function is accurate enough for all meaningful levels of ability relative to the test, especially when the number of test items is relatively small (e.g., less than 50). In the present paper, using the constant information model and constant amounts of test information for a finite interval of ability, simulated data were produced for eight different levels of ability and for twenty different numbers of test items ranging between 10 and 200. Analyses of these data suggest that it is desirable to consider some modification of the test information function when it is used as the measure of accuracy in ability estimation.     

Points of view analysis revisited: Fitting multidimensional structures to optimal distance components with cluster restrictions on the variables

Points of view analysis (PVA), proposed by Tucker and Messick in 1963, was one of the first methods to deal explicitly with individual differences in multidimensional scaling, but at some point was apparently superceded by the weighted Euclidean model, well-known as the Carroll and Chang INDSCAL model. This paper argues that the idea behind points of view analysis deserves new attention, especially as a technique to analyze group differences. A procedure is proposed that can be viewed as a streamlined, integrated version of the Tucker and Messick Process, which consisted of a number of separate steps. At the same time, our procedure can be regarded as a particularly constrained weighted Euclidean model. While fitting the model, two types of nonlinear data transformations are feasible, either for given dissimilarities, or for variables from which the dissimilarities are derived. Various applications are discussed, where the two types of transformation can be mixed in the same analysis; a quadratic assignment framework is used to evaluate the results.The research of the first author was supported by the Royal Netherlands Academy of Arts and Sciences (KNAW); the research of the second author by the Netherlands Organization for Scientific Research (NWO Grant 560-267-029). An earlier version of this paper was presented at the European Meeting of the Psychometric Society, Leuven, 1989. We wish to thank Willem J. Heiser for his stimulating comments to earlier versions of this paper, and we are grateful to the Editor and anonymous referees for their helpful suggestions.     

A latent trait model for dichotomous choice data

The PARELLA model is a probabilistic parallelogram model that can be used for the measurement of latent attitudes or latent preferences. The data analyzed are the dichotomous responses of persons to stimuli, with a one (zero) indicating agreement (disagreement) with the content of the stimulus. The model provides a unidimensional representation of persons and items. The response probabilities are a function of the distance between person and stimulus: the smaller the distance, the larger the probability that a person will agree with the content of the stimulus. An estimation procedure based on expectation maximization and marginal maximum likelihood is developed and the quality of the resulting parameter estimates evaluated.I gratefully acknowledge Ivo Molenaar and Wijbrandt van Schuur for their advice and encouragement during the course of the investigation, Derk-Jan Kiewiet who constructed the program for the ML estimator for the person parameter and Anne Boomsma, Wendy Post, Tom Snijders, and David Thissen for their comments on smaller aspects of the investigation.     

The role of Improv in enhancement of Meaning in Life in youth: An explanatory sequential design

“A global mental health crisis” was sparked by the pandemic, especially for the youth as it exposed them to serious existential crises related to grief, loss, death and dying, deep psychological insecurities, etc. Additionally, this crisis came as a call for greater meaning in the personal and professional lives of youth. To deal with these issues in youth, Improv intervention is being used as an effective contemporary psychological technique to improve holistic perspective-taking. This pilot study investigated the efficacy of Improv intervention in enhancing Meaning in Life in youth using an explanatory sequential design. The sample comprised 80 youth (age range 18–25 years). The study was carried out in two phases—quantitative and qualitative. In the quantitative phase, a randomised control trial design was used to assess the efficacy of the intervention; this was followed by semistructured interviews to identify crucial themes that highlighted participants’ perceptions of Meaning in Life and the benefits of the intervention. Results revealed potential usefulness of Improv in Meaning enhancement.     

算法决策趋避的过程动机理论

算法常用于决策, 但相较于由人类做出的决策, 即便内容相同, 算法决策更容易引起个体反应的分化, 此即算法决策趋避。趋近指个体认为算法的决策比人类的更加公平、含有更少的偏见和歧视、也更能信任和接受, 回避则与之相反。算法决策趋避的过程动机理论用以解释趋避现象, 归纳了人与算法交互所经历的原初行为互动、建立类社会关系和形成身份认同三个阶段, 阐述了各阶段中认知、关系和存在三种动机引发个体的趋避反应。未来研究可着眼于人性化知觉、群际感知对算法决策趋避的影响, 并以更社会性的视角来探究算法决策趋避的逆转过程和其他可能的心理动机。     

Ordinal state-trait regression for intensive longitudinal data

In many psychological studies, in particular those conducted by experience sampling, mental states are measured repeatedly for each participant. Such a design allows for regression models that separate between- from within-person, or trait-like from state-like, components of association between two variables. But these models are typically designed for continuous variables, whereas mental state variables are most often measured on an ordinal scale. In this paper we develop a model for disaggregating between- from within-person effects of one ordinal variable on another. As in standard ordinal regression, our model posits a continuous latent response whose value determines the observed response. We allow the latent response to depend nonlinearly on the trait and state variables, but impose a novel penalty that shrinks the fit towards a linear model on the latent scale. A simulation study shows that this penalization approach is effective at finding a middle ground between an overly restrictive linear model and an overfitted nonlinear model. The proposed method is illustrated with an application to data from the experience sampling study of Baumeister et al. (2020, Personality and Social Psychology Bulletin, 46, 1631).     

Exploring the peer status prototypes: A large-scale latent profile analysis on high-school students from four European countries

Peer status – the regard other group members have of an individual – is fundamental for youth development. Different research traditions developed independent theoretical frameworks conceiving the dimensions underlying social status, and this led to identifying a variety of peer status prototypes. In this work, we explored whether a classification based on the four dimensions of popularity, aggression, dislike, and victimization could integrate the scattered peer status profiles found in the different traditions. A latent profile analysis on 16,224 European students identified the peer status prototypes of popular, bullies, disliked, victims, and average students. Both the peer- and self-reported correlates supported that the five profiles accounted for the large variety of the students' profiles in the literature. These findings suggest that the adoption of a multidimensional approach supported by advanced statistical procedures could identify students' peer status profiles more effectively, replacing classifications based on cutoffs, and leading to a unified students' classification.     

Shaping EU Attitudes Through Identity Leadership: Investigating Pro-EU and EU-Skeptic Identity Narratives

The European Union (EU) faces many challenges. Chief among them are (1) the growing electoral appeal of EU-skeptic parties, (2) the prevalence of negative narratives about the EU, and (3) frequent marginalization of government leaders openly advocating EU membership. It is hence unsurprising that the EU attitude literature focuses heavily on ways in which leaders undermine (rather than bolster) confidence in the EU. The aim of this conceptual article is to fill this void and to shine a spotlight on how leaders seek to restore confidence in the EU. Rather than to merely describe what pro-EU leaders say in public, we propose a conceptual model that combines older EU attitude research (into “nested” social identities and perceived identity compatibility), with more recent social psychology research (into “identity mobilization” and “identity leadership”). By combining insights from both fields, our framework enables us to gain a deeper understanding of why certain pro-EU narratives can be expected to “take hold” and instill faith in the EU among the public at large. The discussion focuses on the implications for EU leadership.