Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

“均”与“寡”阶段性变动下中国居民公平感的变迁

利用中国综合社会调查和中国社会状况综合调查重复截面数据,通过年龄-时期-队列模型对居民公平感的时代变化进行分析。研究发现公平感在年龄上呈“J”型趋势;从时期效应看, 2008年公平感较高, 2010～2013年在低谷徘徊,2015年以后又开始回升;从队列视角看,建国前出生队列公平感偏低,建国后初期的队列相对较高,“50”后有所下滑,从“60”后开始公平感持续走低,到“80”后跌入低谷,但“90”后又开始升高。从1949年前后“寡且不均”到建国初期阶段的“寡且均”,再到改革开放40年快速经济增长下“不寡但不均”的社会变迁过程影响了居民的公平感。     

跨期选择的变易程度正向预测中华文化圈国民的自评扛疫成效：亚非欧美大洋洲18国跨国研究

跨期选择是对不同时间点的得失的权衡与选择。伊索寓言《蚂蚁和蚱蜢》假借群居型昆虫的跨期选择偏爱暗喻投资未来的慢策略比只顾眼前的快策略更利于生存。用跨期选择领域通用的语言解读这一寓言便是：选择大而迟选项的蚂蚁比选择小而早选项的蚱蜢更可能扛过严冬而生存下来。为了探索何种跨期选择策略更有助于我们扛过疫情,本研究调查了亚非欧美大洋洲这5大洲18个国家共计26355名受测者对混合得失双结果的跨期选择偏爱,测量了人们平时和疫时跨期选择偏爱的变易程度(2类变易的程度指标),以及人们自评的扛疫成效。跨文化比较结果的主要发现是：不同通货的选择变易程度(指标1)和不同时期的选择变易程度(指标2)能联合预测中国/新加坡文化圈国民的自评扛疫成效;不同时期的选择变易程度(指标2)也可以单独预测印度/马来西亚/菲律宾/尼日利亚文化圈国民的自评扛疫成效;这2类选择偏爱变易的程度指标不能预测其他文化圈国民的自评扛疫成效(或者预测方向和假设相反)。基于易经“穷则变,变则通”的要旨和跨国比较的发现,我们认为：面临历史危机时善于变通的特长抑或成就了中华民族特有的竞争优势;在应对危机时,与中国文化距离越相近的国家或民族抑或也能...     

Stolen elections: How conspiracy beliefs during the 2020 American presidential elections changed over time

Conspiracy beliefs have been studied mostly through cross-sectional designs. We conducted a five-wave longitudinal study (N = 376; two waves before and three waves after the 2020 American presidential elections) to examine if the election results influenced specific conspiracy beliefs and conspiracy mentality, and whether effects differ between election winners (i.e., Biden voters) versus losers (i.e., Trump voters) at the individual level. Results revealed that conspiracy mentality kept unchanged over 2 months, providing first evidence that this indeed is a relatively stable trait. Specific conspiracy beliefs (outgroup and ingroup conspiracy beliefs) did change over time, however. In terms of group-level change, outgroup conspiracy beliefs decreased over time for Biden voters but increased for Trump voters. Ingroup conspiracy beliefs decreased over time across all voters, although those of Trump voters decreased faster. These findings illuminate how specific conspiracy beliefs are, and conspiracy mentality is not, influenced by an election event.     

Self-control: An integrative framework

Research on self-control has flourished within the last two decades, with many researchers trying to answer one of the most fundamental questions regarding human behaviour—how do we successfully regulate desires in the pursuit of long-term goals? While recent research has focused on different strategies to enhance self-control success, we still know very little about how strategies are implemented or where the need for self-control comes from in the first place. Drawing from parallel fields (e.g., emotion regulation, health) and other theories of self-regulation, we propose an integrative framework that describes self-control as a dynamic, multi-stage process that unfolds over time. In this review, we first provide an overview of this framework, which poses three stages of regulation: the identification of the need for self-control, the selection of strategies to regulate temptations, and the implementation of chosen strategies. These regulatory stages are then flexibly monitored over time. We then expand this framework by outlining a series of growth points to guide future research. By bridging across theories and disciplines, the present framework improves our understanding of how self-control unfolds in everyday life.     

Distress,wellbeing, and growth amidst COVID-19: Considering the dynamic interplay between positive and negative anticipatory emotions

Although negative anticipatory emotions are typically seen as risk factors for poorer psychological outcomes over COVID-19, emotion theorists suggest that this risk may be attenuated if balanced by the experience of positive emotion. Thus, the current study examined whether interactions between positive and negative anticipatory emotions were concurrently associated with psychological distress and greater personal wellbeing/posttraumatic growth (PTG) at three distinct periods (i.e., pre-lockdown, during lockdown, post-lockdown), and whether associations varied by these three COVID-19 time periods. The study utilizes two large longitudinal Australian samples, surveyed in 2020 prior to, during, and after a strict 4-month lockdown that occurred in Australia. Overall, positive emotions attenuated the adverse psychological outcomes arising from higher levels of negative emotion (i.e., higher psychological distress and lower personal wellbeing). Observed effects varied according to COVID-19 threat exposure. Specifically, the interaction was significantly associated with psychological distress prior to the lockdown for Sample 2, and during the lockdown for both samples. The interaction was significantly associated with wellbeing (Sample 2) prior to, and during, the lockdown but only marginally associated post-lockdown. The interaction, however, was not significantly associated with PTG (Sample 1). The results suggest that it is valuable for future research to consider greater emotional complexity (i.e., mixed emotions) over COVID-19, and other stressors more generally, to encompass a more nuanced understanding of resilience.     

The factor structure of the Multiple Affect Adjective Check List-Revised (MAACL-R): Some statistical considerations

In response to Zuckerman's comments on my factor analyses of the MAACL-R, I focus on the statistical issues of the cutoff criterion for factor loadings and the evidence for the discriminant validity of the five-factor solution. Based upon the conclusions I draw in these two areas, I recommend that researchers either (a) use the two factor solution to the MAACL-R represented in the summary scores of Dysphoria and Positive Affect + Sensation Seeking or (b) include all MAACL-R scales in their studies and analyze their data to determine whether it is statistically appropriate to report results from a single scale (A, D, H, PA, or SS) rather than from the summary scores.     

Testing a stochastic foraging model in an operant simulation: Agreement with qualitative but not quantitative predictions

An operant simulation of foraging through baited and empty patches was studied with 4 pigeons. On a three-key panel, side keys were designated as patches, and successive opportunities to complete 16 fixed-ratio 10 schedules on side keys were defined as encounters with feeders. In a random half of the patches in any session, some of the fixed-ratio 10 schedules yielded reinforcement (baited feeders) and the other schedules yielded nonreinforcement (empty feeders). In the other half of the patches, all feeders were empty. Pigeons could travel between patches at any time by completing a fixed-ratio schedule on the center key. An optimal foraging model was tested in Experiments 1 and 2 by varying center-key travel time and number of baited feeders in baited patches. The ordinal predictions that number of feeders visited in empty patches would increase with travel time and decrease as number of baited feeders increased were supported, but pigeons visited far more feeders in empty patches than the optimal number predicted by the model to maximize energy/time. In Experiment 3, evidence was found to suggest that the number of empty feeders encountered before the first baited feeder in baited patches is an important factor controlling leaving empty patches.     

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.