Testing two variances for superiority/non-inferiority and equivalence: Using the exhaustion algorithm for sample size allocation with cost

The equality of two group variances is frequently tested in experiments. However, criticisms of null hypothesis statistical testing on means have recently arisen and there is interest in other types of statistical tests of hypotheses, such as superiority/non-inferiority and equivalence. Although these tests have become more common in psychology and social sciences, the corresponding sample size estimation for these tests is rarely discussed, especially when the sampling unit costs are unequal or group sizes are unequal for two groups. Thus, for finding optimal sample size, the present study derived an initial allocation by approximating the percentiles of an F distribution with the percentiles of the standard normal distribution and used the exhaustion algorithm to select the best combination of group sizes, thereby ensuring the resulting power reaches the designated level and is maximal with a minimal total cost. In this manner, optimization of sample size planning is achieved. The proposed sample size determination has a wide range of applications and is efficient in terms of Type I errors and statistical power in simulations. Finally, an illustrative example from a report by the Health Survey for England, 1995–1997, is presented using hypertension data. For ease of application, four R Shiny apps are provided and benchmarks for setting equivalence margins are suggested.     

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e.g., grand mean centering) when examining effects of level-2 predictors. The primary purpose of this paper is to show that this is a dangerous practice. When level-specific effects of level-1 variables differ, failing to disaggregate them can severely bias estimation of level-2 predictor slopes. We show mathematically why this is the case and highlight factors that can exacerbate such bias. We corroborate these findings with simulations and present an empirical example, showing how such distortions can severely alter substantive conclusions. We ultimately recommend that simply including the cluster mean of the level-1 variable as a control will alleviate the problem.     

Assessing Representations of Close Relationships Among Chinese and Japanese Adolescents and Young Adults: Commonalities and Differences in the Two Confucian Cultures

This article proposed an affective relationships model with its assessment instrument and examined how Chinese and Japanese adolescents and young adults construct mental representations of their close relationships, and the influence of Confucian cultural beliefs on these representations. The participants were 1,565 students aged 14 to 24 years living in China or Japan. The students were asked about their relationships with four figures: mother, father, closest friend, and romantic partner. We found that: (a) adolescents and young adults in both cultures constructed constellations of relationships containing multiple figures, and they articulated reasons for each figure's significance; and (b) there were between-group differences in the relationships with the father and the romantic partner for Chinese versus Japanese adolescents and young adults. These differences were partly explained by the influence of Confucianism on the Chinese participants’ cultural beliefs that retained the patriarchal values.     

Examining the item response process to personality measures in high-stakes situations: Issues of measurement validity and predictive validity

We conducted two experimental studies with between-subjects and within-subjects designs to investigate the item response process for personality measures administered in high- versus low-stakes situations. Apart from assessing measurement validity of the item response process, we examined predictive validity; that is, whether or not different response models entail differential selection outcomes. We found that ideal point response models fit slightly better than dominance response models across high- versus low-stakes situations in both studies. Additionally, fitting ideal point models to the data led to fewer items displaying differential item functioning compared to fitting dominance models. We also identified several items that functioned as intermediate items in both the faking and honest conditions when ideal point models were fitted, suggesting that ideal point model is “theoretically” more suitable across these contexts for personality inventories. However, the use of different response models (dominance vs. ideal point) did not have any substantial impact on the validity of personality measures in high-stakes situations, or the effectiveness of selection decisions such as mean performance or percent of fakers selected. These findings are significant in that although prior research supports the importance and use of ideal point models for measuring personality, we find that in the case of personality faking, though ideal point models seem to have slightly better measurement validity, the use of dominance models may be adequate with no loss to predictive validity.     

A double-edged sword: How social diversity affects trust in representatives via perceived competence and warmth

Previous research has claimed that diversity erodes trust, even though the empirical evidence is mixed and restricted to ethnic neighborhood diversity. Against the backdrop of increasing diversity within the political sphere and concurrently declining political trust, we examined the impact of social diversity on trust in groups of political representatives. In two experiments (N₁ = 109, N₂ = 248) we tested how the diversity of political parties affected citizens’ trust in them. In line with predictions of the stereotype content model, diverse parties were perceived as warmer and less competent than non-diverse parties (Experiments 1–2). Additionally, party diversity was perceived as having more benefits, but also involving more threats (Experiment 2). Consequently, diversity had both positive (via warmth and benefits) and negative (via competence and threats) indirect effects on trust. These results help to untangle previously mixed, for the most part non-experimental, findings of the relationship between diversity and trust.     

Facet-level analysis of the relations between personality and laboratory aggression

Multiple reviews and meta-analyses have identified the low pole of the Five-Factor Model (FFM) Agreeableness (also called Antagonism) as the primary domain-level personality correlates of aggression across self-report and behavioral methodologies. In the current study, we expand on this literature by investigating the relations between FFM facets and aggressive behavior as measured by laboratory competitive reaction time tasks (CRTTs). Across three samples (total N = 639), we conducted weighted mean analyses, multiple regression analyses, and dominance analyses to determine which FFM facets were the strongest predictors of aggression within and across domains. These analyses suggested that facets of Agreeableness were among the strongest consistent predictors of CRTT aggression, including Sympathy (r = −.21) and Cooperation (r = −.14), but facets from other FFM domains also yielded meaningful relations (e.g., Anger from Neuroticism; r = .17). We conclude by discussing these results in the context of controversies surrounding laboratory aggression paradigms and emphasizing the importance of considering small effect sizes in the prediction of societally harmful behavior like aggression.     

Assessing the Intersectionality of Religious and Sexual Identities During the Coming-Out Process

Lesbian, gay, and bisexual (LGB) individuals often experience internalized and/or externalized religious rejection due to their sexual orientation. Initial steps in the coming-out process can be especially difficult and can result in existential crises, including questioning one's place within the religious/spiritual realm. The authors propose a developmental framework for conceptualizing the role of religion and spirituality in the coming-out process. Cass's (1979, 1984) stage model of coming out and Genia's (1995) model of religious development, along with additional literature addressing LGB spirituality, serve as foundations for this framework. Counseling and research implications of the framework are also discussed.     

留守初中生同伴侵害与攻击性的关系:链式多重中介模型

为探究留守初中生同伴侵害与攻击性的关系机制,通过构建链式多重中介模型,考察歧视知觉、孤独感和心理韧性在二者关系中的多重中介效应。采用问卷调查法对519名留守初中生进行调查,结果显示：（1）留守初中生同伴侵害的发生率为96.3%,具有普遍性;（2）留守初中生同伴侵害、歧视知觉、孤独感、心理韧性与攻击性之间均呈显著相关;（3）留守初中生的歧视知觉、孤独感和心理韧性在其同伴侵害与攻击性的关系中具有链式多重中介作用;（4）同伴侵害与攻击性关系模型具有一定稳定性,同时在是否留守及单亲与双亲外出留守初中生群体中存在显著差异。研究结果揭示了同伴侵害与攻击性的关系机制,可为探索留守初中生不良同伴关系的教育策略提供参考。