Combining mixture distribution and multidimensional IRTree models for the measurement of extreme response styles

Personality constructs, attitudes and other non-cognitive variables are often measured using rating or Likert-type scales, which does not come without problems. Especially in low-stakes assessments, respondents may produce biased responses due to response styles (RS) that reduce the validity and comparability of the measurement. Detecting and correcting RS is not always straightforward because not all respondents show RS and the ones who do may not do so to the same extent or in the same direction. The present study proposes the combination of a multidimensional IRTree model with a mixture distribution item response theory model and illustrates the application of the approach using data from the Programme for the International Assessment of Adult Competencies (PIAAC). This joint approach allows for the differentiation between different latent classes of respondents who show different RS behaviours and respondents who show RS versus respondents who give (largely) unbiased responses. We illustrate the application of the approach by examining extreme RS and show how the resulting latent classes can be further examined using external variables and process data from computer-based assessments to develop a better understanding of response behaviour and RS.     

Multilevel analysis of matching behavior

Multilevel modeling has been considered a promising statistical tool in the field of the experimental analysis of behavior and may serve as a convenient statistical analysis for matching behavior because it structures data in groups (or levels) to account simultaneously for the within‐subject and between‐subject variances. Heretofore, researchers have sometimes pooled data erroneously from different subjects in a single analysis by using average ratios, average response and reinforcer rates, aggregation of subjects, etc. Unfortunately, this leads to loss of information and biased estimations, which can severely undermine generalization of the results. Instead, a multilevel approach is advocated to combine several subjects' matching behavior. A reanalysis of previous data on matching behavior is provided to illustrate the method and point out its advantages. It illustrates that multilevel regression leads to better estimations, is more convenient, and offers more behavioral information. We hope this paper will encourage the use of multilevel modeling in the statistical practices of behavior analysts.     

Poisson Multilevel Models with Small Samples

Recent methodological studies have investigated the properties of multilevel models with small samples. Previous work has primarily focused on continuous outcomes and little attention has been paid to count outcomes. The estimation of count outcome models can be difficult because the likelihood has no closed-form solution, meaning that approximation methods are required. Although adaptive Gaussian quadrature (AGQ) is generally seen as the gold standard, its comparative performance has been investigated with larger samples. AGQ approximates the full likelihood, a function that is known to produce biased estimates with small samples with continuous outcomes. Conversely, penalized quasi-likelihood (PQL) is considered to be a less desirable approximation; however, it can approximate the restricted likelihood function, a function that is known to perform well with smaller samples with continuous outcomes. The goal of this paper is to compare the small sample bias of full likelihood methods to the linearization bias of PQL with restricted likelihood. Simulation results indicate that the linearization bias of PQL is preferable to the finite sample bias of AGQ with smaller samples.     

Students' Ethical Decision‐Making When Considering Boundary Crossings With Counselor Educators

Counselor education students (N = 224) rated 16 boundary‐crossing scenarios involving counselor educators. They viewed boundary crossings as unethical and were aware of power differentials between the 2 groups. Next, they rated the scenarios again, after reviewing 1 of 4 ethical informational resources: relevant standards in the ACA Code of Ethics (American Counseling Association, 2014), 2 different boundary‐crossing decision‐making models, and a placebo. Although participants rated all resources except the placebo as moderately helpful, these resources had little to no influence on their ethical decision‐making. Only 47% of students in the 2 ethical decision‐making model groups reported they would use the model they were exposed to in the future when contemplating boundary crossings     

Does attitude acquisition in evaluative conditioning without explicit CS-US memory reflect implicit misattribution of affect?

Research that dissociates different types of processes within a given task using a processing tree approach suggests that attitudes may be acquired through evaluative conditioning in the absence of explicit encoding of CS-US pairings in memory. This research distinguishes explicit memory for the CS-US pairings from CS-liking acquired without encoding of CS-US pairs in explicit memory. It has been suggested that the latter effect may be due to an implicit misattribution process that is assumed to operate when US evocativeness is low. In the present research, the latter assumption was supported neither by two high-powered experiments nor by complementary meta-analytic evidence, whereas evocativeness exerted an influence on explicit memory. This pattern of findings is inconsistent with the view that CS-liking acquired without encoding of CS-US pairs in explicit memory reflects an implicit misattribution process at learning. Hence, the underlying learning process is awaiting further empirical scrutiny.     

适应性时间管理：死亡意识对时间知觉和跨期决策的影响

死亡意识是个体对自身死亡必然性的认识; 基于进化适应性的考量, 作者认为具有前瞻性的死亡意识作为人类特有的认知能力和个体生命史的终极坐标, 不仅可能引起恐惧感和防御反应, 更重要的是可以帮助人们做出适应性的时间管理。据此推论, 死亡意识的启动会加强人们对时间有限性的关注, 体验出更强的时间流逝感, 影响人们对时间的评估, 以及人们对不同时间点的成本与收益进行权衡而做出的跨期决策。本研究采用死亡凸显范式启动死亡意识, 通过两个实验探讨了死亡意识、时间知觉和跨期决策三者之间的关系。结果发现, 死亡意识启动使被试低估时间距离, 并表现出较低的跨期决策延迟折扣率, 从而在较小的即时获益与更大的延迟的获益之间更为偏好未来导向的选项。进一步的分析显示, 时间知觉在死亡意识和跨期决策延迟折扣率之间起到部分中介变量的作用。以上的研究结果初步揭示了死亡意识在时间管理上的适应性价值。     

The stability of self-esteem variability: A real-time assessment

The present study investigates stability and variability as distinct features of state self-esteem change. The amount of variance attributable to stable individual differences, the association between successive self-esteem experiences, and situational and/or person × situation interaction effects were estimated in repeated measures of self-esteem whilst considering measurement invariance. N = 160 adolescents reported momentary self-esteem in an experience sampling study, (i.e., three assessments a day, over a 2-day period). Latent state-trait analysis indicate that change in state self-esteem is a stable process largely determined by interindividual differences in trait self-esteem, while the impact of occasion-specific influences is small. These intrinsic dynamics ensure consistent self-referential experiences. Results reveal experience sampling as a suitable method to track short-term changes of self-esteem.     

A stronger latent‐variable methodology to actual–ideal discrepancy

We introduce a latent actual–ideal discrepancy (LAID) approach based on structural equation models (SEMs) with multiple indicators and empirically weighted variables. In Study 1, we demonstrate with simulated data, the superiority of a weighted approach to discrepancy in comparison to a classic unweighted one. In Study 2, we evaluate the effects of actual and ideal appearance on physical self‐concept and self‐esteem. Actual appearance contributes positively to physical self‐concept and self‐esteem, whereas ideal appearance contributes negatively. In support of multidimensional perspective, actual‐ and ideal‐appearance effects on self‐esteem are substantially—but not completely—mediated by physical self‐concept. Whereas this pattern of results generalises across gender and age, multiple‐group invariance tests show that the effect of actual appearance on physical self‐concept is larger for women than for men. Copyright © 2008 John Wiley & Sons, Ltd.     

Future‐biased search: the quest for the ideal

Decision‐makers with ideal candidates already in mind often extend search beyond optimal endpoints when searching for the best option among a sequential list of alternatives. Extended search is investigated here using three laboratory experiments; individuals in these tasks exhibit future‐bias, delaying choice beyond normative benchmarks. Searchers' behavior is consistent with setting high thresholds based on a focal ideal outcome without full attention to its probability or the value of second‐best alternatives; the behavior is partially debiased by manipulating which outcomes are in the searchers' focal set. Documenting future‐bias in sequential search tasks offers new insights for understanding self‐control and intertemporal choice by providing a situation in which thresholds may be set too high and myopic behavior does not prevail. Copyright © 2008 John Wiley & Sons, Ltd.     

The Metaphysics of Causal Models

This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late pre?mption and other cases that have proved problematic for causal models.