Notes

Stratifying for Worth: An Updated Inhabitants Hazard to health Stratification Method.
We discuss how findings inform theory, setting an agenda for future research on the collaborative roots of dishonesty. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
There are two potentially useful but nonintersecting efforts to help ensure that psychological science produces valid and credible information and contributes to the understanding of diverse human experiences. Whereas North American ethnic minority psychology research/cultural diversity science (EM/D) emphasizes cultural competency to yield contextualized psychological understanding of understudied and underserved minority populations, current open science (OS) approaches emphasize material and data sharing, and statistical proficiency to maximize the replicability of mainstream findings. To illuminate the extent of and explore reasons for this bifurcation, and OS's potential impact on EM/D, we conducted three studies.

In Study 1, we reviewed editorial/publishing policies and empirical articles appearing in four major EM/D journals on the incentives for and use of OS. Journals varied in OS-related policies; 32 of 823 empirical articles incorporated any OS practices. Study 2 was a national mixed-methods suA, all rights reserved).Anxiety and depressive symptoms are common, comorbid, and consequential for adolescents. Attachment theory suggests that styles of relationships with parents, developed from patterns of interactions over time, contribute to risk for these internalizing symptoms. This may be especially relevant for high-risk, clinically severe adolescents. However, most research focuses primarily on attachment relationships to mothers. Some theoretical perspectives also suggest that attachment to other caregivers (such as fathers) may not only be uniquely important for understanding internalizing symptoms but may also interact with maternal attachment. Therefore, it is important to examine these attachment relationships in tandem. The present study examines associations between attachment and internalizing symptoms in a sample of 1,141 youth (12-20 years old; 54.0% female, 96.5% White) from a multisite residential treatment facility. Youth reported on attachment anxiety and avoidance with both parents, as well as anxiety and depressive symptoms. Response surface analyses were used to examine curvilinear, interactive, and fit effects using a model comparison approach. Overall, for patterns of anxious attachment, the best-fitting models reflected simple additive and linear effects. For avoidant attachment, best-fitting models included interactions and fit patterns, suggesting the meaning of maternal attachment was dependent on paternal and vice versa. After accounting for covariates, however, maternal attachment was the sole predictor in most models except attachment avoidance predicting depressive symptoms. These results have implications for attachment theory and research, and further work untangling these complex effects may inform clinical practice for high-risk adolescents. (PsycInfo Database Record (c) 2022 APA, all rights reserved).This study examined aspirations for future long-term committed relationships, marriage, and parenthood in a sample of 392 racially diverse sexual and gender minority (SGM) youth assigned female at birth (AFAB) aged 16-20. Differences by gender identity, sexual identity, and race/ethnicity were assessed, as were associations with contextual variables including minority stressors, SGM community involvement, perceived partner availability, and relationship experiences. Results showed that the majority of SGM-AFAB youth viewed long-term committed relationships as important and likely, whereas only about half of participants had high aspirations to get married and have children someday. Those who did view marriage and parenthood as important perceived that it is feasible for them to achieve these outcomes someday. These constructs did not differ by race/ethnicity. There were differences by gender identity and sexual identity, such that cisgender women reported higher aspirations for marriage and parenthood than did gender minorities, and those with binary sexual identities reported higher aspirations for marriage than did those with nonbinary sexual identities. Examination of the contextual variables revealed that relationship experience variables were the most consistently associated with aspirations for committed relationships, marriage, and parenthood. In contrast, victimization and perceived partner availability were not associated with any of the family formation aspirations. As SGM individuals are increasingly granted legal rights affecting their ability to marry and form families, research is needed to help inform efforts to promote their relationship health while considering that they may have unique aspirations for relationships, marriage, and parenthood compared to the general public. (PsycInfo Database Record (c) 2022 APA, all rights reserved).Concerns about replication failures can be partially recast as concerns about excessive heterogeneity in research results. Although this heterogeneity is an inherent part of science (e.g., sampling variability; studying different conditions), not all heterogeneity results from unavoidable sources. In particular, the flexibility researchers have when designing studies and analyzing data adds additional heterogeneity. This flexibility has been the topic of considerable discussion in the last decade. Ideas, and corresponding phrases, have been introduced to help unpack researcher behaviors, including researcher degrees of freedom and questionable research practices. Using these concepts and phrases, methodological and substantive researchers have considered how researchers' choices impact statistical conclusions and reduce clarity in the research literature. While progress has been made, inconsistent, vague, and overlapping use of the terminology surrounding these choices has made it difficult to have clear conversations about the most pressing issues. Further refinement of the language conveying the underlying concepts can catalyze further progress. We propose a revised, expanded taxonomy for assessing research and reporting practices. In addition, we redefine several crucial terms in a way that reduces overlap and enhances conceptual clarity, with particular focus on distinguishing practices along two lines research versus reporting practices and choices involving multiple empirically supported options versus choices known to be subpar. We illustrate the effectiveness of these changes using conceptual and simulated demonstrations, and we discuss how this taxonomy can be valuable to substantive researchers by helping to navigate this flexibility and to methodological researchers by motivating research toward areas of greatest need. (PsycInfo Database Record (c) 2022 APA, all rights reserved).Statistical network models describing multivariate dependency structures in psychological data have gained increasing popularity. Such comparably novel statistical techniques require specific guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding the estimation of networks and their accuracy. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency. (PsycInfo Database Record (c) 2022 APA, all rights reserved).Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT), which uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of (a) network structure, (b) edge (connection) strength, and (c) global strength. Performance of NCT is evaluated in simulations that show NCT to perform well in various circumstances for all three tests The Type I error rate is close to the nominal significance level, and power proves sufficiently high if sample size and difference between networks are substantial. We illustrate NCT by comparing depression symptom networks of males and females. learn more Possible extensions of NCT are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).Careful consideration of the tradeoff between Type I and Type II error rates when designing experiments is critical for maximizing statistical decision accuracy. Typically, Type I error rates (e.g., .05) are significantly lower than Type II error rates (e.g., .20 for .80 power) in psychological science. Further, positive findings (true effects and Type I errors) are more likely to be the focus of replication. This conventional approach leads to very high rates of Type II error. Analyses show that increasing the Type I error rate to .10, thereby increasing power and decreasing the Type II error rate for each test, leads to higher overall rates of correct statistical decisions. This increase of Type I error rate is consistent with, and most beneficial in the context of, the replication and "New Statistics" movements in psychology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).An evaluation of a difference between effect sizes from two dependent variables in a single study is likely to be based on differences between standard scores if raw scores on those variables are not scaled in comparable units of measurement. The standardization used for this purpose is usually sample-based rather than population-based, but the consequences of this distinction for the construction of confidence intervals on differential effects have not been systematically examined. In this article I show that differential effect confidence intervals (CIs) constructed from differences between the standard scores produced by sample-based standardization can be too narrow when those effects are large and dependent variables are highly correlated, particularly in within-subjects designs. I propose a new approach to the construction of differential effect CIs based on differences between adjusted sample-based standard scores that allow conventional CI procedures to produce Bonett-type CIs (Bonett, 2008) on individual effects. Computer simulations show that differential effect CIs constructed from adjusted standard scores can provide much better coverage probabilities than CIs constructed from unadjusted standard scores. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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