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The COVID-19 pandemic has extensively changed the state of psychological science from what research questions psychologists can ask to which methodologies psychologists can use to investigate them. In this article, we offer a perspective on how to optimize new research in the pandemic's wake. Because this pandemic is inherently a social phenomenon-an event that hinges on human-to-human contact-we focus on socially relevant subfields of psychology. We highlight specific psychological phenomena that have likely shifted as a result of the pandemic and discuss theoretical, methodological, and practical considerations of conducting research on these phenomena. After this discussion, we evaluate metascientific issues that have been amplified by the pandemic. We aim to demonstrate how theoretically grounded views on the COVID-19 pandemic can help make psychological science stronger-not weaker-in its wake.

This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be performed from start to finish.

The Negative Year in School Effect (NYiSE) claims that grade-relative-to-age influences academic self-concept. Being young for your grade is associated with lower self-concept, whereas being old for your grade is associated with higher self-concept. We extend this research in several ways. First, we aim to improve causal claims for the NYiSE by utilizing birth month as an instrumental variable. Using the Longitudinal Study of Australian Youth we find that the NYiSE is negative under instrumental variable regression. Given that NYiSE has focused on math self-concept we show that the effect extends to other measures of math, general academic, and English social comparison. Finally, using General Estimating Equations we show that the NYiSE also has an effect on university entry that is explained by self-beliefs. Our research has policy implications around how children enter school. Further, this research shows that the use of alternative causal modeling strategies is a useful asset to educational research especially when randomized control trials are not yet available or feasible.

Testing of directional dependence is a method to infer causal direction that recently has attracted some attention. Previous examples by e.g. von Eye and DeShon (2012a) and extensive simulation studies by Pornprasertmanit and Little (2012) have demonstrated that under specific assumptions, directional-dependence tests can recover the true causal direction between two variables. Simulation results are important in the evaluation of any statistical method, but they are necessarily less complex than real data that come with potential irregularities (e.g. departures from linearity, presence of confounders, etc.). In this article, we evaluate the performance of directional-dependence tests using benchmark data consisting of 65 variable pairs with known causal order. We find that between 21% and 43% of all cases are correctly classified using different directional-dependence tests that rely on differences in skew, kurtosis, or a combined measure. We then examine some of the assumptions of the directional-dependence test and find that for virtually all variable pairs, some assumptions are violated. When only pairs in which assumptions are fulfilled are selected, performance of all directional-dependence tests improves. We probe whether particular features of the variable pairs impact whether a test yields a correct or incorrect result, but find no strong predictors. Our findings provide a complimentary picture to previously conducted simulation studies, and highlight the fact that directional-dependence tests are prone to causal classification errors when key assumptions are violated. Such violations are potentially common in real data.

Existing gap-year research indicates a number of benefits of a gap-year at the end of school and before university enrollment. Life span theory of control, however, suggests that direct goal investment, rather than delay, at developmental transitions is associated with more adaptive outcomes. Comparing these perspectives, the authors undertook 2 studies: 1 in Finland (N = 384, waves = 3) and 1 in Australia (N = 2,259, waves = 5) both with an initial time wave in the last year of high school. The authors explored the effects of a gap-year on both psychological and attainment outcomes using an extensive propensity score matching technique. The Finnish study found no difference in growth in goal commitment, effort, expectations of attainment and strain, or in actual university enrollment in those planning to enter university directly versus those who plan to take a gap-year. The Australian study found no difference in growth in outlooks for the future and career prospects, and life satisfaction between gap-year youth and direct university entrants. However, the study did find that gap-year students were more likely to drop out of a university degree. Implication for theory and practice are discussed.

Thirty-four English–Malay bilinguals of between four and six years of age (both balanced and dominant) characterized as low socioeconomic status (SES) on income and parental education were tested on the child-Attentional Network Task (child-ANT; Rueda, Fan, McCandliss, Halparin, Gruber, Lercari & Posner, 2004) measuring executive attention. Although SES measures fell below the Singapore median, Malay children's performance on the child-ANT remained high when compared to other age-matched monolingual and bilingual children previously tested with the child-ANT (Yang, Yang & Lust, 2011), and English–Chinese Singaporean bilinguals (Kang, 2009). None of the three SES measures – father's and mother's education, and income, significantly correlated with child-ANT components. Regression analyses confirmed that none of the SES measures significantly predicted performance on the child-ANT. Caregiver reports suggested that both balanced and dominant bilinguals displayed high executive control. We consider the possibility that cultural variations – simultaneous and pervasiveness of bilingualism in Singapore, or pervasive code-switching – may ameliorate potential negative effects of SES on executive control development. [ABSTRACT FROM AUTHOR]

Based on the social investment principle and theories of social relationship differentiation, the present study was conducted to investigate whether personality differences in high school predict young adults' living arrangements (with roommates or a romantic partner, alone, or staying with parents) 2 years later (selection) and whether these different social contexts provoke long-term personality changes (socialization). Using data from a 3-wave longitudinal study of 8,052 high school graduates in Germany, multinomial logistic regression analyses revealed substantial selection effects of the Big Five traits on living arrangements. Propensity score matching was applied to provide a strong test of the socialization effects of these living arrangements. Young adults who lived with roommates showed increases in Openness but the smallest increases in Conscientiousness. Living with a romantic partner was the most beneficial arrangement for the development of Conscientiousness. These results highlight the importance of social contexts for personality development in young adulthood.

Ding and Miratrix [1] recently concluded that adjustment on a pre-treatment covariate is almost always preferable to reduce bias. I extend the examined parameter space of the models considered by Ding and Miratrix, and consider slight extensions of their models as well. Similar to the conclusion by Pearl [7], I identify constellations in which bias due to adjustment, or failing to adjust is symmetrical, but also confirm some findings of Ding and Miratrix.

This study investigated the accuracy of several early literacy measures that have been used in research and practice for first grade reading screening. A set of measures, Word Identification Fluency (WIF), Letter Naming Fluency, Phoneme Segmentation Fluency, and Nonsense Word Fluency, were administered as screening measures with 138 first grade students in the fall of the school year. Reading skills were assessed at the end of first grade using Oral Reading Fluency, the Test of Word Reading Efficiency (Sight Word Efficiency and Phonemic Decoding Efficiency), reading Maze, and a latent variable composite. Analyses compared the accuracy at which each screening measure, as well as combinations of screening measures, classified students according to successful or unsuccessful reading outcomes at the end of the year. Receiver operating characteristic curve analyses indicated that when compared with other single screening measures, WIF tended to demonstrate the strongest overall classification accuracy. With levels of sensitivity held constant at 0.90, combining screening measures with WIF using predicted probabilities from logistic regression analyses resulted in modest improvements in accuracy by reducing the number of false positives. More measures were not always better, however, as models of two or three measures were as accurate as models consisting of all measures. Overall results provided support for WIF as a starting point for first grade reading screening, whereby additional steps might be taken to reduce false positives. (Contains 2 footnotes and 4 tables.)

Research Findings: Parental expressivity, child physiological regulation (indexed by respiratory sinus arrhythmia suppression), child behavioral regulation, and child adjustment outcomes were examined in 45 children (M age = 4.32 years, SD = 1.30) and their parents. With the exception of child adjustment (i.e., internalizing and externalizing problems and adaptive skills), which were assessed with parents' ratings, all variables were observed behaviorally or physiologically. A 3-path mediation path model was tested with the relations between parental expressivity and child adjustment outcomes mediated through child physiological regulation and behavioral regulation. Despite low power to detect the mediated effect, there was evidence to suggest that physiological regulation and behavioral regulation were 2 mediating mechanisms by which parental high positive/low negative expressivity may influence adaptive skills. Thus, parental expressivity may shape children's physiological regulation. And physiological regulation may be 1 mechanism by which effortful control becomes manifested as behavioral regulation that becomes apparent to others who then make evaluations about individuals' adaptive skills. Practice or Policy: The results have implications for interventions aimed at parent training or parental coaching of emotion as well as interventions aimed at enhancing children's social-emotional or behavioral regulation to improve children's adaptive skills. (Contains 1 figure, 3 tables, and 5 footnotes.)

In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across clusters. We examine the underlying assumptions of these modeling choices and the type of randomized experiment approximated by each approach. Using a simulation study, we compare the relative performance of these modeling and conditioning choices in reducing bias due to confounding variables at both the person and cluster levels. An applied example based on a study by Hughes, Chen, Thoemmes, and Kwok (2010) is provided in which the effect of retention in Grade 1 on passing an achievement test in Grade 3 is evaluated. We find that models that consider the clustered nature of the data both in estimation of the propensity score and conditioning on the propensity score performed best in our simulation study; however, other modeling choices also performed well. The applied example illustrates practical limitations of these models when cluster sizes are small. (Contains 1 figure, 1 footnote, and 4 tables.)

The association between grade retention in first grade and passing the third grade state accountability tests, the Texas Assessment of Knowledge and Skills (TAKS) reading and math, was investigated in a sample of 769 students who were recruited into the study when they were in first grade. Of these 769 students, 165 were retained in first grade and 604 were promoted. Using propensity matching, we created five imputed datasets (average N = 321) in which promoted and retained students were matched on 67 comprehensive covariates. Using GEE models, we obtained the association between retention and passing the third grade TAKS reading and math tests. The positive association between retention and math scores was significant, whereas the association was marginally significant for reading scores. (Contains 1 note and 4 tables.)

Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on the identification of threats to validity and the inclusion of design features that may prevent those threats from occurring or render them implausible. Rubin's approach focuses on the precise specification of both the possible outcomes for each participant and assumptions that are mathematically sufficient to estimate the causal effect. In this article, the authors compare the perspectives provided by the 2 approaches on randomized experiments, broken randomized experiments in which treatment nonadherence or attrition occurs, and observational studies in which participants are assigned to treatments on an unknown basis. The authors highlight dimensions on which the 2 approaches have different emphases, including the roles of constructs versus operations, threats to validity versus assumptions, methods of addressing threats to internal validity and violations of assumptions, direction versus magnitude of causal effects, role of measurement, and causal generalization. The authors conclude that investigators can benefit from drawing on the strengths of both approaches in designing research. (Contains 3 tables, 3 figures, and 13 footnotes.)

Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well-known technique of generating a large number of samples in a Monte Carlo study, and estimating power as the percentage of cases in which an estimate of interest is significantly different from zero. Examples of power calculation for commonly used mediational models are provided. Power analyses for the single mediator, multiple mediators, 3-path mediation, mediation with latent variables, moderated mediation, and mediation in longitudinal designs are described. Annotated sample syntax for M"plus" is appended and tabled values of required sample sizes are shown for some models. (Contains 6 figures, 4 tables, and 2 footnotes.)

Religiosity, especially religious fundamentalism, is often assumed to have an inherent connection with conservative politics. This article proposes that the relationship varies by race in the United States. In Study 1, race moderated the relationships between religiosity indicators and political alignment in a nationally representative sample. In Study 2, the effect replicated in a student sample with more reliable measures. Among both Black and Latino Americans, the relationship between religiosity and conservative politics is far weaker than it is among White Americans, and it is sometimes altogether absent. In Study 3, a tradition-focused view of religion was found to more strongly mediate the link between religiosity and political attitudes among Whites than it did among Blacks and Latinos. It is argued that the relationship between religiosity and political alignment is best understood as a product of cultural-historical conditions associated with group memberships. Keywords: race; culture; fundamentalism; religion; conservatism; political attitudes

Integrative complexity broadly measures the structural complexity of statements. This breadth, although beneficial in multiple ways, can potentially hamper the development of specific theories. In response, the authors developed a model of complex thinking, focusing on 2 different ways that people can be complex within the integrative complexity system and subsequently developed measurements of each of these 2 routes: Dialectical complexity focuses on a dialectical tension between 2 or more competing perspectives, whereas elaborative complexity focuses on complexly elaborating on 1 singular perspective. The authors posit that many variables have different effects on these 2 forms of complexity and subsequently test this idea in 2 different theoretical domains. In Studies 1a, 1b, and 2, the authors demonstrate that variables related to attitude strength (e.g., domain importance, extremism, domain accessibility) decrease dialectical complexity but increase elaborative complexity. In Study 3, the authors show that counterattitudinal lying decreases dialectical complexity but increases elaborative complexity, implicating a strategic (as opposed to a cognitive strain) view of the lying-complexity relationship. The authors argue that this dual demonstration across 2 different theoretical domains helps establish the utility of the new model and measurements as well as offer the potential to reconcile apparent conflicts in the area of cognitive complexity. Keywords: integrative complexity, dialectical complexity, elaborative complexity, attitude strength, lying