The Ethical Use of Fit Indices in Structural Equation Modeling: Recommendations for Psychologists

Croon and van Veldhoven discussed a model for analyzing micro–macro multilevel designs in which a variable measured at the upper level is predicted by an explanatory variable that is measured at the lower level. Additionally, the authors proposed an approach for estimating this model. In their approach, estimation is carried out by running a regression analysis on Bayesian Expected a Posterior (EAP) estimates. In this article, we present an extension of this approach to interaction and quadratic effects of explanatory variables. Specifically, we define the Bayesian EAPs, discuss a way for estimating them, and we show how their estimates can be used to obtain the interaction and the quadratic effects. We present the results of a “proof of concept” via Monte Carlo simulation, which we conducted to validate our approach and to compare two resampling procedures for obtaining standard errors. Finally, we discuss limitations of our proposed extended Bayesian EAP-based approach.

https://www.mdpi.com/2227-7390/10/5/842/pdf?version=1646648927

A Bayesian EAP-Based Nonlinear Extension of Croon and Van Veldhoven’s Model for Analyzing Data from Micro–Macro Multilevel Designs

/pdf/the-meaning-of-respect-under-varying-context-conditions-40xobxow0u.pdf

The meaning of respect under varying context conditions

Living with cultural, religious, and ideological diversity inevitably creates situations where people are confronted with beliefs, values, or practices that they disapprove of. In such situations, people may consider reasons to nevertheless tolerate what they disapprove of (i.e., forbearance tolerance), or reject these (i.e., intolerance). In the current review, we consider empirical research on the processes of intergroup tolerance and consider different manifestations of (in)tolerance. Then we discuss recent work on the dual process model of tolerance, which considers intuitive versus deliberative objections to cultural, religious, and ideological differences, and how these can be overridden to produce tolerance. We then review literature on the boundaries of tolerance including the role of moralization and moral values, before considering individual difference factors and situations of threat that can hamper intergroup tolerance. We conclude by considering five areas ripe for future exploration on the social psychology of intergroup tolerance and intolerance. 

The social psychology of intergroup tolerance and intolerance

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than conventional maximum likelihood confirmatory factor analysis. Using a non-clinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We found additional support for the validity of the three-factor model of the IIP by including external criteria-Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism-in the analysis. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores and weighted sum scores. We found excellent reliability (with R tt ≥ 0.90) for Dominance, Love, and Distress for the two scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlational pattern with the external measures was in line with theoretical expectations and similar to the results from the factor analysis. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

/pdf/bayesian-and-maximum-likelihood-modeling-and-higher-level-1cnh8b1o30.pdf

Bayesian and Maximum-Likelihood Modeling and Higher-Level Scores of Interpersonal Problems With Circumplex Structure.

Our outline points out three aspects of a new
post-modern methodology in psychology: liberal, pluralistic, and
more tolerant: liberal because it rejects rules that are too strict
in favor of more freedom in the choice of method, pluralistic
because it conveys an “almost anything goes” attitude toward
methods, and more tolerant because mutual tolerance among
researchers is vital for a pluralism of methods. Psychological
phenomena are complex and can best be understood by using
diﬀerent methods. However,
to get things working, tolerance must actively be lived. Of course,
much depends on our own willingness as researchers but also on
the system’s arrangements. Psychology could be more colorful,
and we could all have more fun if we were to be more committed
to such a methodology.

/pdf/regarding-an-almost-anything-goes-attitude-toward-methods-in-5304d889gy.pdf

Regarding an “Almost Anything Goes” Attitude Toward Methods in Psychology

Our own prior research has demonstrated that respect for disapproved others predicts and might foster tolerance toward them. This means that without giving up their disapproval of others’ way of li...

https://journals.sagepub.com/doi/pdf/10.1177/01461672211024422

Lukas Loreth

Papers

Regarding an “Almost Anything Goes” Attitude Toward Methods in Psychology

Does Respect Foster Tolerance? (Re)analyzing and Synthesizing Data From a Large Research Project Using Meta-Analytic Techniques:

Supplementary materials to: The meaning of respect under varying context conditions

The meaning of respect under varying context conditions