Assessment of dispositional forgiveness in adolescence: a contribution to the Italian validation of the Forgiveness Likelihood Scale

ABSTRACT

The current study investigated the factor structure, factorial invariance, and reliability of the Italian version of the Forgiveness Likelihood Scale (FLS) among 604 adolescents in Italy (217 boys and 387 girls) with a mean age of 16.6 years (SD?=?1.3). The FLS is a 10-item Likert-type scale created to assess the predisposition to forgive across situations. The sample was randomly split into two subsamples to investigate the FLS structure. Results indicated a unidimensional structure, and factorial invariance was found for the factor solution across gender. Scale reliability was adequate, revealing appropriate internal consistency (α?=?.75). Evidence for convergent validity was also found. The results suggested that the Italian version of the FLS can be reliably used to measure forgiveness among Italian adolescents. Practice implications and future research directions are discussed.     

Evaluating fit of the Prospective and Retrospective Memory Questionnaire (PRMQ) in a Nigerian adult population

This study aimed to evaluate the latent structure of the Prospective and Retrospective Memory Questionnaire (PRMQ) and to estimate the reliability and validity of scores from the measure in a Nigerian adult population (N = 758; age range = 18 - 63 years; females = 52.24%). Respondents also completed the Cognitive Failures Questionnaire (CFQ). The data were analysed utilising confirmatory factor analysis (CFA). The results suggest the PRMQ to have a tripartite structure characterised by the following features: general memory, plus eight prospective and eight retrospective memory items. Scores from the PRMQ had evidence of convergent validity with the CFQ. The reliability of scores from the PRMQ was of acceptable magnitude for the research purposes investigated in the study.     

Supervising away from home: clinical,cultural and professional challenges

This paper explores some challenges of supervising clinical work of trainees, known as ‘routers’, who live in countries with diverse cultural, social and political traditions, and the analysts who travel to supervise them. It is written as an evolving dialogue between the authors, who explore together the effects of their own culture of origin, and in particular the legacy and values of their own training institutes on the styles and models of analytic supervision. Their dialogue is framed around the meaning of home and experiences of homesickness for analysts working away from home in an interactive field of strangeness in countries where analytical psychology is a relatively new discipline. The authors outline the findings from their own qualitative survey, where other supervisors working abroad, and those they have supervised, describe their experiences and their encounters with difference. The dialogue ends with both authors discussing what they have learned about teaching and supervising abroad, the implications for more flexible use of Jungian concepts, and how such visits have changed their clinical practice in their home countries.     

Using a Few Snapshots to Distinguish Mountains from Waves: Weak Factorial Invariance in the Context of Trait-State Research

In this article, we show that the underlying dimensions obtained when factor analyzing cross-sectional data actually form a mix of within-person state dimensions and between-person trait dimensions. We propose a factor analytical model that distinguishes between four independent sources of variance: common trait, unique trait, common state, and unique state. We show that by testing whether there is weak factorial invariance across the trait and state factor structures, we can tackle the fundamental question first raised by Cattell; that is, are within-person state dimensions qualitatively the same as between-person trait dimensions? Furthermore, we discuss how this model is related to other trait-state factor models, and we illustrate its use with two empirical data sets. We end by discussing the implications for cross-sectional factor analysis and suggest potential future developments.     

Might “unique” factors be “common”? On the possibility of indeterminate common–unique covariances

The present paper shows that the usual factor analytic structured data dispersion matrix Λ Ψ Λ′ + Δ can readily arise from a set of scores y = Λ η + ε, where the “common” (η) and “unique” (ε) factors have nonzero covariance: Γ = Covε,η) ≠ 0. Implications of this finding are discussed for the indeterminacy of factor scores, and for the issue of invariance of factor analytic covariance models. The size of the problem is explored with numerical examples. I would like to acknowledge the large amount of effort and stimulating input supplied on the previous drafts of this paper from the reviewers, Associate Editor, and Editors of Psychometrika. Particular thanks go to William Meredith for his assistance with the final draft. Requests for reprints should be sent to Dave Grayson, 14 Poplar Grove, Lawson, NSW 2783, Australia     

Framing experts' (dis)agreements about uncertain environmental events

Agreements and disagreements between expert statements influence lay people's beliefs. But few studies have examined what is perceived as a disagreement. We report six experiments where people rated agreement between pairs of probabilistic statements about environmental events, attributed to two different experts or to the same expert at two different points in time. The statements differed in frame, by focusing on complementary outcomes (45% probability that smog will have negative health effects vs. 55% probability that it will not have such effects), in probability level (45% vs. 55% probability of negative effects), or in both respects. Opposite frames strengthened disagreement when combined with different probability levels. Approximate probabilities can be “framed” in yet another way by indicating reference values they are “over” or “under”. Statements that use different directional verbal terms (over vs. under 50%) indicated greater disagreement than statements with the same directional term but different probability levels (over 50% vs. over 70%). Framing and directional terms similarly affected consistency judgments when both statements were issued by the same expert at different occasions. The effect of framing on perceived agreement was significant for medium (10 and 20 percentage points) differences between probabilities, whereas the effect of directional term was stable for numerical differences up to 40 percentage points. To emphasize agreement between different estimates, they should be framed in the same way. To accentuate disagreements or changes of opinion, opposite framings should be used.     

Dimensional structure and measurement invariance of the BRIEF-2 across gender in a socially vulnerable sample of primary school-aged children

The present study aims to analyze, on the one hand, the dimensional structure of the BRIEF-2 and, on the other, its measurement invariance across gender in a sample of primary school-aged children. Participants were 168 students (51.8% girls) in conditions of social risk and in foster homes, with ages ranging from 6 to 15 years old (M = 10.08; SD = 2.09). The children’s executive functioning level was obtained from their parents or caregivers. The analysis of the internal structure using confirmatory factor analysis reveals that the model with three indexes (Behavioral, Emotional and Cognitive) and nine scales (Inhibit, Shift, Self-Monitor, Emotional Control, Initiate, Working Memory, Plan/Organize, Organization of Materials and Task-Monitor) showed a good fit to the sample. Likewise, the results support the measurement invariance of the BRIEF-2 across genders. The coefficient alpha values for the index scores ranged from .71 to .91, with coefficients for the individual scales ranging from .66 to .88. The findings support the factorial validity of the BRIEF-2 scores, suggesting that it is an adequate instrument to evaluate executive functioning reported by parents and caregivers. Future studies must continue to examine the structure and invariance of the BRIEF-2 in different populations and cultures.     

Evaluating Factorial Invariance: An Interval Estimation Approach Using Bayesian Structural Equation Modeling

In this study, we introduce an interval estimation approach based on Bayesian structural equation modeling to evaluate factorial invariance. For each tested parameter, the size of noninvariance with an uncertainty interval (i.e. highest density interval [HDI]) is assessed via Bayesian parameter estimation. By comparing the most credible values (i.e. 95% HDI) with a region of practical equivalence (ROPE), the Bayesian approach allows researchers to (1) support the null hypothesis of practical invariance, and (2) examine the practical importance of the noninvariant parameter. Compared to the traditional likelihood ratio test, simulation results suggested that the proposed Bayesian approach could offer additional insight into evaluating factorial invariance, thus, leading to more informative conclusions. We provide an empirical example to demonstrate the procedures necessary to implement the proposed method in applied research. The importance of and influences on the choice of an appropriate ROPE are discussed.     

A widely applicable extension of the random effects two-way layout: Its definition and statistical analysis based on group invariance

A type of data layout that may be considered as an extension of the two-way random effects analysis of variance is characterized and modeled based on group invariance. The data layout seems to be suitable for several scenarios in psychometrics, including the one in which multiple measurements are taken on each of a set of variables, and the measurements can be divided into exchangeable subsets. The algebraic structure of the model is studied, which leads to results that are applicable to such problems as estimating correlation matrix corrected for attenuation and testing symmetry hypotheses.The author would like to thank NIH for support through grants M01 RR00044 and P01 DE13539, and NSF and ASA Survey Section for a travel grant which allowed him to present this paper as an invited young researcher at the Conference in Celebration of Wayne A. Fuller's 70th birthday.     

二阶因素模型的测量等价性检验——以大学生网络利他行为量表为例

与一阶因素模型相比,二阶因素模型具有较多优点,但二阶因素模型的测量等价性检验要更复杂,它需要依次进行七个不同水平的检验：形等价、一阶弱等价、二阶弱等价、一阶强等价、二阶强等价、二阶严等价和一阶严等价。低水平的等价性满足之后,才能进行更为严格的高一水平的等价性检验。运用均值和协方差结构（MACS）模型对大学生网络利他行为量表（IABSU）进行二阶因素模型的测量等价性检验,结果表明,IABSU具有跨地域的完全一阶、二阶严等价性。