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Objective: The symmetry principle and the frame-of-reference perspective have each made contributions to improving the measurement of personality. Although each perspective is valuable in its own right, we argue that even greater improvement can be achieved through the combination of both. Therefore, the goal of the current article was to show the value of a combined lens-model and frame-of-reference perspective., Method: We conducted a literature review to summarize relevant research findings that shed light on the interplay of both perspectives and developed an integrative model., Results: Based on the literature review and on theoretical grounds, we argue that a basic premise of the frame-of-reference literature--that personality items are open to interpretation and allow individuals to impose their own contextual framings--should be considered from a symmetry perspective. Unintended context-specificity in items may "spread" to personality facets and domains, and thus, impact the symmetry of personality measures with other criteria. As the individuals´ frames-of-reference and (a)symmetric relationships are not always apparent, we term them as "hidden.", Conclusions: The proposed combination of lens-model and frame-of-reference perspectives provides further insights into current issues in personality research and uncovers important avenues for future research., (© 2020 The Authors. Journal of Personality published by Wiley Periodicals LLC.)

Daily diaries and other everyday experience methods are increasingly used to study relationships between two time-varying variables X and Y. Although daily data potentially often have weekly cyclical patterns (e.g., stress may be higher on weekdays and lower on weekends), the majority of daily diary studies have ignored this possibility. In this study, we investigated the effect of ignoring existing weekly cycles. We reanalyzed an empirical dataset (stress and alcohol consumption) and performed Monte Carlo simulations to investigate the impact of omitting weekly cycles. In the empirical dataset, ignoring cycles led to the inference of a significant within-person X-Y relation whereas modeling cycles suggested that this relationship did not exist. Simulation results indicated that ignoring cycles that existed in both X and Y led to bias in the estimated within-person X-Y relationship. The amount and direction of bias depended on the magnitude of the cycles, magnitude of the true within-person X-Y relation, and synchronization of the cycles. We encourage researchers conducting daily diary studies to address potential weekly cycles in their data. We provide guidelines for detecting and modeling cycles to remove their influence and discuss challenges of causal inference in daily experience studies., (© 2015 Wiley Periodicals, Inc.)

Traditional statistical analyses can be compromised when data are collected from groups or multiple observations are collected from individuals. We present an introduction to multilevel models designed to address dependency in data. We review current use of multilevel modeling in 3 personality journals showing use concentrated in the 2 areas of experience sampling and longitudinal growth. Using an empirical example, we illustrate specification and interpretation of the results of series of models as predictor variables are introduced at Levels 1 and 2. Attention is given to possible trends and cycles in longitudinal data and to different forms of centering. We consider issues that may arise in estimation, model comparison, model evaluation, and data evaluation (outliers), highlighting similarities to and differences from standard regression approaches. Finally, we consider newer developments, including 3-level models, cross-classified models, nonstandard (limited) dependent variables, multilevel structural equation modeling, and nonlinear growth. Multilevel approaches both address traditional problems of dependency in data and provide personality researchers with the opportunity to ask new questions of their data., (© 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.)

Recent field studies have revived the hypothesis that low self-esteem causes aggression. Accordingly, we reanalyzed the data from a previous experiment and conducted a new experiment to study direct physical aggression in the form of blasting a fellow participant with aversive noise. We also conducted a field study using a measure of indirect aggression in the form of a consequential negative evaluation. High narcissists were more aggressive than others but only when provoked by insult or humiliation and only toward the source of criticism. The combination of high self-esteem and high narcissism produced the highest levels of aggression. These results support the view of aggression as stemming from threatened egotism and are inconsistent with the hypothesis that low self-esteem causes either direct or indirect aggression.

Multitrait-multimethod analyses were used to examine the degree of convergent and discriminant validity of the Big Five. Phase 1 examined self-reports of the Big Five across three measurement occasions. Self-reports of the Big Five traits were stable, but were moderately intercorrelated. Phase 2 examined assessments of the Big Five across different types of informants (self, peer, and parent). Assessments converged across types of informants and, importantly, there was no evidence of correlation between the Big Five traits across the perspectives of different types of informants. The present results suggest that the degree of orthogonality of the Big Five traits depends on the source of the data. A single informant produces Big Five traits that are intercorrelated, whereas diverse informants tend to produce a much more orthogonal structure. Discussion focuses on methodological considerations in examining levels of convergent and discriminant validity and the theoretical implications for understanding personality assessments and the relationship between three-and five-factor models of personality.

Personality correlates of older women's perceived susceptibility to breast cancer, heart disease, and osteoporosis were examined in a community sample of 312 women aged 40-86. A latent factor of general perceived susceptibility to disease was shown to underlie disease-specific perceptions of susceptibility. Affect-related personality traits (neuroticism, extraversion, optimism, worry, and self-deceptive enhancement) and internal and chance health locus of control predicted general perceived susceptibility. Perceived disease characteristics (e.g., perceived controllability, severity) and the use of cognitive heuristics (i.e., perceived similarity to those who contract each disease) also displayed marked consistency across the three distinct diseases. Finally, our results suggested that general beliefs about the characteristics of health threats and the use of cognitive heuristics may mediate the link between personality traits and perceived risk.

Although theories of personality emphasize the integrative, enduring, and dynamic nature of personality, the current modal research design in personality ignores the dimension of time. We consider a variety of recent methods of longitudinal data analysis to examine both short-term and long-term development and change in personality, including mean-level analyses both across and within individuals across time, variance structures across time, and cycles and dynamic models across time. These different longitudinal analyses can address classic as well as new questions in the study of personality and its development. We discuss the linkages among different longitudinal analyses, measurement issues in temporal data, the spacing of assessments, and the levels of generalization and potential insights afforded by different longitudinal analyses.

This study examined whether children's cognitive appraisal biases moderate the impact of stressful divorce-related events on psychological adjustment in 355 children ages 9 to 12, whose families had experienced divorce within the past 2 years. Multiple regression indicated that endorsement of negative cognitive errors for hypothetical divorce events moderates the relations between stressful divorce events and self- and maternal reports of internalizing and externalizing symptoms, but only for older children. Positive illusions buffer the effects of stressful divorce events on child-reported depression and mother-reported externalizing problems. Implications of these results for theories of stress and coping, as well as for interventions for children of divorced families, are discussed.

Temperament has been conceptualized as an important predictor of children's psychological adjustment. However, even with reliable and valid measures, there is the additional problem of overlapping item content across measures of temperament and symptoms that threatens the interpretability of such associations. This study assessed this possible confounding using both confirmatory factor analysis (CFA) and expert ratings. A number of items from temperament measures of negative and positive emotionality, impulsivity, and attention focusing were shown to overlap with items measuring depressive and conduct problem symptoms. CFAs demonstrated that temperament could be reliably measured after eliminating overlapping items. Negative emotionality and impulsivity showed a positive relation to symptom measures, whereas positive emotionality and attention showed a negative relation to symptom measures. The pattern of associations indicated consistent relations between negative emotionality and depression and between impulsivity and conduct problems. The results show that even after removal of the threat to validity presented by overlap in measures, there continue to be significant, interpretable relations between temperament and symptoms.

This article introduces the Journal of Personality's special issue on the life voyage of Dodge Morgan who, in 1986 at the age of 54, sailed solo around the world in 150 days. Before the voyage, Morgan agreed to participate in an intensive psychological case study, the data for which provide the focus for this special issue. William Nasby and Nancy W. Read have organized the vast array of psychological data obtained from Morgan and produced a complex and illuminating interpretation of his life, drawing liberally from the five-factor trait model of personality and the life-story model of adult identity. This introduction provides a historical and intellectual context for Nasby and Read's study by considering the various ways in which personality psychologists have employed the case study in research and examining the many conceptual and methodological problems and possibilities that arise in the psychological study of the single case.

Dispositional and situational measures of children's coping were developed using a theoretically based approach. Two studies (N1 = 217; N2 = 303) assessed the psychometric characteristics of these measures in fourth- through sixth-grade children. Confirmatory factor analyses indicated that a four-factor model of dispositional coping (active, distraction, avoidant, and support seeking) provided a better fit to the data than either the problem- versus emotion-focused (Lazarus & Folkman, 1984) or passive versus active (Billings & Moos, 1981) coping models. The four-factor model was largely invariant with respect to age and gender. Moderate to high correlations were found between the parallel subscales of the dispositional and situational measures of coping. Although the four factor structures of the dispositional and situational measures were generally similar, factor loadings and correlations between dimensions were not equivalent.

This study investigated the appraisals of the significance of negative events made by 256 preadolescent children of divorce. Appraisals were assessed by a 24-item self-report scale. Confirmatory factor analysis of this scale found support for a 3-dimensional model: negative self-appraisal, negative other-appraisal, and material loss. Differentiation between the dimensions of appraisal increased with age in both cross-sectional and over-time data. Evidence for convergent and discriminant validity of the self-report measure of appraisals was found with scores derived from children's open-ended descriptions of their appraisals. Cross-sectional structural equation models found significant paths between negative appraisal and psychological symptoms, over and above the direct effects of the traditional life event measure of stress. Structural equation modeling of longitudinal (5.5 months) data found a significant path from Time 1 appraisal to Time 2 anxiety for the older children.

Theories hypothesizing interactions between a categorical and one or more continuous variables are common in personality research. Traditionally, such hypotheses have been tested using nonoptimal adaptations of analysis of variance (ANOVA). This article describes an alternative multiple regression-based approach that has greater power and protects against spurious conclusions concerning the impact of individual predictors on the outcome in the presence of interactions. We discuss the structuring of the regression equation, the selection of a coding system for the categorical variable, and the importance of centering the continuous variable. We present in detail the interpretation of the effects of both individual predictors and their interactions as a function of the coding system selected for the categorical variable. We illustrate two- and three-dimensional graphical displays of the results and present methods for conducting post hoc tests following a significant interaction. The application of multiple regression techniques is illustrated through the analysis of two data sets. We show how multiple regression can produce all of the information provided by traditional but less optimal ANOVA procedures.

The authors conducted a cross-sectional and prospective longitudinal study of stress, coping, and psychological symptoms in children of divorce. The sample consisted of 258 children (mean age = 10.1; SD = 1.2), of whom 196 were successfully followed 5.5 months later. A 4-dimensional model of coping was found using confirmatory factor analysis, with the factors being active coping, avoidance, distraction, and support. In the cross-sectional model avoidance coping partially mediated the relations between negative events and symptoms while active coping moderated the relations between negative events and conduct problems. In the longitudinal model significant negative paths were found from active coping and distraction Time 1 to internalizing symptoms Time 2, while Time 1 support coping had a positive path coefficient to Time 2 depression. Positive paths were found between negative events at Time 1 and anxiety at Time 2, and between all symptoms at Time 1 and negative events at Time 2.

Consensus in personality judgment refers to the agreement with which two people (or more) can describe the personality of another; self-other agreement refers to the similarity between personality descriptions by the self and by others; and accuracy refers to the degree to which personality descriptions capture real attributes of the persons described. After years of focusing on other subjects, researchers recently have renewed their interest in these three topics. Current empirical research is philosophically diverse and includes studies incorporating pragmatic, constructivist, and realist approaches. Other research is resolving long-standing methodological problems and providing new analytic techniques for the study of consensus, self-other agreement, and accuracy. This special issue includes articles exemplifying all of these research approaches and documents that a new wave of research on consensus, self-other agreement, and accuracy in personality judgment now comprises a burgeoning field that has finally come of age.

This article reviews statistical issues that arise in temporal data, particularly with respect to daily experience data. Issues related to nonindependence of observations, the nature of data structures, and claims of causality are considered. Through the analysis of data from a single subject, we illustrate concomitant time-series analysis, a general method of examining relationships between two or more series having 50 or more observations. We also discuss detection of and remedies for the problems of trend, cycles, and serial dependency that frequently plague temporal data, and present methods of combining the results of concomitant time series across subjects. Issues that arise in pooling cross-sectional and time-series data and statistical models for addressing these issues are considered for the case in which there are appreciably fewer than 50 observations and a moderate number of subjects. We discuss the possibility of using structural equation modeling to analyze data structures in which there are a large number (e.g., 200) of subjects, but relatively few time points, emphasizing the different causal status of synchronous and lagged effects and the types of models that can be specified for longitudinal data structures. Our conclusion highlights some of the issues raised by temporal data for statistical models, notably the important roles of substantive theory, the question being addressed, the properties of the data, and the assumptions underlying each technique in determining the optimal approach to statistical analysis.

The evaluative tendencies of nondepressed, mildly depressed, and severely depressed individuals are examined in the areas of judgments of contingency, attributions of causality, expectancy estimates, and self-schemata/self-reference. The available empirical literature in these four areas indicates that nondepressed people tend to exhibit positivistic evaluative responses, whereas mildly depressed persons tend to display unbiased (neither positivistic nor negativistic) evaluative response patterns. The available evidence is suggestive of negativistic evaluative tendencies in severely depressed individuals, with this bias being most clearly manifested in the area of self-schemata/self-reference. These results are interpreted in terms of contemporary explanations of depression and recent advances in models of cognitive processing.