Erin M. Buchanan’s research while affiliated with Harrisburg University of Science and Technology and other places

Latent variable modeling as a lens for psychometric theory is a popular tool for social scientists to examine measurement of constructs. Journals, such as Assessment regularly publish articles supporting measures of latent constructs wherein a measurement model is established. Confirmatory factor analysis can be used to investigate the replicability and generalizability of the measurement model in new samples, while multigroup confirmatory factor analysis is used to examine the measurement model across groups within samples. With the rise of the replication crisis and “psychology’s renaissance,” interest in divergence in measurement has increased, often focused on small parameter differences within the latent model. This article presents visualizemi, an R package that provides functionality to calculate multigroup models, partial invariance, visualizations for (non)-invariance, effect sizes for models and parameters, and potential replication rates compared with random models. Readers will learn how to interpret the impact and size of the proposed non-invariance in models with a focus on potential replication and how to plan for registered reports.

In their commentary on Hall et al., Buckwalter and Friedman (2024) claimed that the replication should have been interpreted as successful, argued that the researchers’ conclusions were incorrect, and implied that the replication effort was misguided. As a subset of contributors to the Hall et al. replication, we appreciate the opportunity to respond to their comment. Although we recognize the potential for disagreement in the interpretation of research results, Buckwalter and Friedman’s critique ignored several key features of the research, and many of their arguments and proposed interpretations were already addressed by Hall et al. (2024). In response to their comment, we (a) explain why Hall et al. did not replicate all of the original findings, (b) emphasize how Hall et al. were accurate and nuanced in the description and interpretation of their results, and (c) caution against focusing on the mechanisms underlying a psychological phenomenon before it is clearly established

According to the justified true belief (JTB) account of knowledge, people can truly know something only if they have a belief that is both justified and true (i.e., knowledge is JTB). This account was challenged by Gettier, who argued that JTB does not explain knowledge attributions in certain situations, later called “Gettier-type cases,” wherein protagonists are justified in believing something to be true, but their belief was correct only because of luck. Laypeople may not attribute knowledge to protagonists with justified but only luckily true beliefs. Although some research has found evidence for these so-called Gettier intuitions, Turri et al. found no evidence that participants attributed knowledge in a counterfeit-object Gettier-type case differently than in a matched case of JTB. In a large-scale, cross-cultural conceptual replication of Turri and colleagues’ Experiment 1 (N = 4,724) using a within-participants design and three vignettes across 19 geopolitical regions, we did find evidence for Gettier intuitions; participants were 1.86 times more likely to attribute knowledge to protagonists in standard cases of JTB than to protagonists in Gettier-type cases. These results suggest that Gettier intuitions may be detectable across different scenarios and cultural contexts. However, the size of the Gettier intuition effect did vary by vignette, and the Turri et al. vignette produced the smallest effect, which was similar in size to that observed in the original study. Differences across vignettes suggest that epistemic intuitions may also depend on contextual factors unrelated to the criteria of knowledge, such as the characteristics of the protagonist being evaluated.

The replication crisis in psychology and related sciences contributed to the adoption of large-scale research initiatives known as Big Team Science (BTS). BTS has made significant advances in addressing issues of replication, statistical power, and diversity through the use of larger samples and more representative cross-cultural data. However, while these collaborations hold great potential, they also introduce unique challenges related to their scale. Drawing on experiences from successful BTS projects, we identified and outlined key strategies for overcoming diversity, volunteering, and capacity challenges. We emphasize the need for the implementation of strong organizational practices and the distribution of responsibility to prevent common pitfalls. More fundamentally, BTS requires a shift in mindset toward prioritizing collaborative effort, diversity, transparency, and inclusivity. Ultimately, we call for reflection on the strengths and limitations of BTS to enhance the quality, generalizability, and impact of research across disciplines.

Though people usually imagine the typical person as a man rather than a woman, the effect is mixed for racial groups and understudied among traditionally male social groups (e.g., police and criminals) and non-U.S. populations. Results from a survey (N > 5000) collected via a globally distributed laboratory network in over 40 regions demonstrated that attitudes toward Black people and politicians had a stronger relationship with attitudes toward the men rather than the women of the group. However, attitudes toward White people had a stronger relationship with attitudes toward White women than White men, whereas attitudes toward East Asian people, police officers, and criminals did not have a stronger relationship with attitudes toward either the men or women of each respective group. Regional endorsement of liberal values was explored as a potential moderator. These findings have implications for understanding the unique forms of prejudice women face around the world.

Cultural logic is a set of cultural scripts and patterns organized around a central theme. The cultural logics of dignity, honor, and face describe different ways of evaluating a person’s worth and maintaining cooperation. These cultural logics vary in prevalence across cultures. In this study, we collaboratively develop and validate a measure capturing these cultural logics, which will allow us to map world cultures based on the prevalence of these logics. We will further explore the interrelations of dignity, honor, and face with prosocial behavior, values, moral beliefs, and religiosity as well as examine the generalizability of these relationships across cultures. Finally, we will explore historical antecedents (e.g., resource scarcity) and current correlates (e.g., inequality) of the country-level prevalence of these cultural logics. This study will generate a new dataset of country scores for dignity, honor, and face that will be available for future comparative research. It will also provide theoretical insights for researchers and practitioners interested in cooperation and social behavior within and between cultures.

Objective:To investigate how women with severe migraine disability perceive the impact of migraine on their career options and mobility.Background:It is well documented within literature that more women experience migraine than men. It is also well known there is a pay gap between men and women in workforce, but the effect of migraine on career mobility has not been well studied. Design and Methods:This study was an exploratory electronic survey. Volunteers answered items about career plans and advancements, education, field credentials, socioeconomic success, and they also completed the Migraine Disability Assessment (MIDAS). Results:702 participants completed the survey with 195 participants meeting the needed criteria of being female, employed within the last year, and experiencing severe migraine disability as determined by MIDAS scores. When asked if the participant believed that their migraine disease has hindered their career plan, 81.0% [158/195] felt this way (responses: Sometimes, Often, or Always). Likewise, 66.2% [129/195] felt their career advancement opportunities were hindered (responses: Sometimes, Often, or Always) by their migraine disease. Conclusions:The study found a substantial number of participants believed their migraine hindered career plans, advancement opportunities, and compensation. The researchers also found that many respondents were not working in their field of education/training, and that promotions and raises were limited. The paper advocates for broader demographic representation in future research to enhance generalizability. More research would be needed to develop and bridge the gap between women with migraine and potential differences they experience in the workplace.

Biases in favor of culturally prevalent social ingroups are ubiquitous, but random assignment to arbitrary experimentally created social groups is also sufficient to create ingroup biases (i.e., the minimal group effect; MGE). The extent to which ingroup bias arises from specific social contexts versus more general psychological tendencies remains unclear. This registered report focuses on three questions. First, how culturally prevalent is the MGE? Second, how do critical cultural and individual factors moderate its strength? Third, does the MGE meaningfully relate to culturally salient real-world ingroup biases? We compare the MGE to bias in favor of a family member (first cousin) and a national ingroup member. We propose to recruit a sample of > 200 participants in each of > 50 nations to examine these questions and advance our understanding of the psychological foundations and cultural prevalence of ingroup bias.

In their replication of Turri et al. (2015; Experiment 1), Hall et al. (2024) identified a key condition difference that was not observed in the original experiment. In their commentary, Buckwalter and Friedman (2024) posited that the evidence presented by Hall et al. should be interpreted as fully replicating Turri et al. While Hall et al. may have observed a similar effect size as the one they calculated from Turri et al.’s data, they did not replicate Turri et al.’s statistical results, and their findings were not consistent with Turri et al.’s claims from Experiment 1. Further, Hall et al. presented a nuanced discussion of their findings that acknowledged many of Buckwalter and Friedman critiques. We opine that, through selectively referencing portions of Hall et al.’s results, Buckwalter and Friedman mischaracterize the key findings and conclusions of Hall et al.

In non-experimental studies, causality should not be avoided. Associations are a poor proxy for causal effects if they are not properly adjusted for common causes. However, it is still possible to ask how large bias due to unadjusted common causes can be in support of a causal claim. The bias in a standardised mean difference (d) depends on how strongly the common predisposition, a summary of factors not considered, is related to the factor (convertible into several other effect size measures) and the outcome (scalable as correlation). Actually, the left boundary of the confidence interval for d must exceed the product of these two relations. We present ViSe, an R package and Shiny application that helps to visually constrain these quantities and shows which combinations of the quantities support a causal effect. Such visual sensitivity analysis can be conducted on any published results, or on simple summary or the t-statistics.