Michael Eid

Norms for experiencing emotions in different cultures: inter- and intranational differences.

Within- and between-nations differences in norms for experiencing emotions were analyzed in a cross-cultural study with 1,846 respondents from 2 individualistic (United States, Australia) and 2 collectivistic (China, Taiwan) countries. A multigroup latent class analysis revealed that there were both universal and culture-specific types of norms for experiencing emotions. Moreover, strong intranational variability in norms for affect could be detected, particularly for collectivistic nations. Unexpectedly, individualistic nations were most uniform in norms, particularly with regard to pleasant affect. Individualistic and collectivistic nations differed most strongly in norms for self-reflective emotions (e.g., pride and guilt). Norms for emotions were related to emotional experiences within nations. Furthermore, there were strong national differences in reported emotional experiences, even when norms were held constant.

Subjective well-being and adaptation to life events: A meta-analysis.

Previous research has shown that major life events can have short- and long-term effects on subjective well-being (SWB). The present meta-analysis examines (a) whether life events have different effects on affective and cognitive well-being and (b) how the rate of adaptation varies across different life events. Longitudinal data from 188 publications (313 samples, N = 65,911) were integrated to describe the reaction and adaptation to 4 family events (marriage, divorce, bereavement, childbirth) and 4 work events (unemployment, reemployment, retirement, relocation/migration). The findings show that life events have very different effects on affective and cognitive well-being and that for most events the effects of life events on cognitive well-being are stronger and more consistent across samples. Different life events differ in their effects on SWB, but these effects are not a function of the alleged desirability of events. The results are discussed with respect to their theoretical implications, and recommendations for future studies on adaptation are given.

Latent state–trait theory and research in personality and individual differences

Latent state–trait (LST) theory is a generalization of classical test theory designed to take account of the fact that psychological measurement does not take place in a situational vacuum. The basic concepts of latent state–trait theory (LST theory) are introduced. The core of LST theory consists of two decompositions: (a) the decomposition of any observed score into latent state and measurement error, and (b) the decomposition of any latent state into latent trait and latent state residual representing situational and/or interaction effects. Latent states and latent traits are defined as special conditional expectations. A score on a latent state variable is defined as the expectation of an observable variable Yik given a person in a situation whereas a score on a latent trait variable is the expectation of Yik given a person. The theory also comprises the definition of consistency, occasion specificity, reliability, and stability coefficients. An overview of different models of LST theory is given. It is shown how different research questions of personality psychology can be and have been analysed within the LST framework and why research in personality and individual differences can profit from LST theory and methodology. Copyright

A multitrait-multimethod model with minimal assumptions

A new model of confirmatory factor analysis (CFA) for multitrait-multimethod (MTMM) data sets is presented. It is shown that this model can be defined by only three assumptions in the framework of classical psychometric test theory (CTT). All other properties of the model, particularly the uncorrelated-ness of the trait with the method factors are logical consequences of the definition of the model. In the model proposed there are as many trait factors as different traits considered, but the number of method factors is one fewer than the number of methods included in an MTMM study. The covariance structure implied by this model is derived, and it is shown that this model is identified even under conditions under which other CFA-MTMM models are not. The model is illustrated by two empirical applications. Furthermore, its advantages and limitations are discussed with respect to previously developed CFA models for MTMM data.

Analytic strategies for understanding affective (in)stability and other dynamic processes in psychopathology.

The dynamics of psychopathological symptoms as a topic of research has been neglected for some time, likely because of the inability of cross-sectional and retrospective reports to uncover the ebb and flow of symptoms. Data gathered with the experience sampling method (ESM) enable researchers to study symptom variability and instability over time as well as the dynamic interplay between the environment, personal experiences, and psychopathological symptoms. ESM data can illuminate these dynamic processes, if time is both considered and integrated into (a) the research question itself, (b) the assessment or sampling method, and (c) the data analytic strategy. The authors highlight the complexity of assessing affective instability and unstable interpersonal relationships and explore sampling and analytic methods. Finally, they propose guidelines for future investigations. For the assessment of affective instability, the authors endorse the use of time-contingent recordings and of instability indices that address temporal dependency. For the assessment of unstable interpersonal relationships, they advocate the use of event-contingent recordings and separate analyses within and across dyads.

Comparing Typological Structures Across Cultures By Multigroup Latent Class Analysis A Primer

The advantages of latent class analysis for cross-cultural research in psychology are discussed. The basic principles of multigroup latent class analysis are described and illustrated by an empirical study comparing satisfaction-with-life-domain profiles across two nations (China, United States). In particular, it is shown how various assumptions of measurement invariance across cultures can be tested statistically in the latent class framework.

Structural equation modeling of multitrait-multimethod data: Different models for different types of methods.

The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods used) should guide the choice of the statistical model to analyze the data. In this respect, the authors distinguish between (a) interchangeable methods, (b) structurally different methods, and (c) the combination of both kinds of methods. The authors present an appropriate model for each type of method. All models allow separating measurement error from trait influences and trait-specific method effects. With respect to interchangeable methods, a multilevel confirmatory factor model is presented. For structurally different methods, the correlated trait-correlated (method-1) model is recommended. Finally, the authors demonstrate how to appropriately analyze data from MTMM designs that simultaneously use interchangeable and structurally different methods. All models are applied to empirical data to illustrate their proper use. Some implications and guidelines for modeling MTMM data are discussed.

Separating "Rotators" From "Nonrotators" in the Mental Rotations Test: A Multigroup Latent Class Analysis

Items of mental rotation tests can not only be solved by mental rotation but also by other solution strategies. A multigroup latent class analysis of 24 items of the Mental Rotations Test (MRT) was conducted in a sample of 1,695 German pupils and students to find out how many solution strategies can be identified for the items of this test. The results showed that five subgroups (latent classes) can be distinguished. Although three of the subgroups differ mainly in the number of items reached, one class shows are very low performance. In another class, a special solution strategy is used. This strategy seems to involve analytic rather than mental rotation processes and is efficient only for a special MRT item type, indicating that not all MRT items require a mental rotation approach. In addition, the multigroup analysis revealed significant sex differences with respect to the class assignment, confirming prior findings that on average male participants perform mental rotation tasks faster and better than female participants. Females were also overrepresented in the analytic strategy class. The results are discussed with respect to psychometric and substantive implications, and suggestions for the optimization of the MRT items are provided.

Is attention to feelings beneficial or detrimental to affective well-being? Mood regulation as a moderator variable.

This research examined the functionality of attention to feelings for affective well-being. The authors found that mood regulation, but not clarity of feelings, moderated the attention-well-being relationship. For individuals with high mood regulation scores, attention was beneficial to affective well-being, whereas for individuals with low mood regulation scores, attention was detrimental to affective well-being. This finding was corroborated by self- and peer reports in Study 1 and replicated in Study 2. The validity of the scales was established by the convergence of self- and peer ratings. Moreover, Study 2 showed that dysfunctional and functional and self consciousness scales suppressed variance in attention to feelings, thereby revealing that attention incorporates both adaptive and maladaptive aspects.

CORTISOL AND BEHAVIOR: 2. APPLICATION OF A LATENT STATE-TRAIT MODEL TO SALIVARY CORTISOL

In two studies we applied a new stochastic model for the measurement of latent states and traits to salivary cortisol in healthy subjects. Data were analyzed by Linear Structural Relations (LISREL). In the first study, 48 students collected saliva samples on two occasions at 1300h with an interval of six weeks between occasions. Salivary cortisol levels were found to be mainly influenced by situational and/or interactional effects, which determined approximately 75% of the total variance of the hormone data, while only approximately 21% were determined by the latent trait. Measurement unreliability was found to be approximately 4%. In the second study, 54 young mothers collected saliva at 0800h, 1500h, and 2000h for three consecutive days, starting on the second day after delivery of a healthy baby. Early morning salivary cortisol showed high consistency across the three days. Approximately 60% of the total variance in the early morning cortisol samples was determined by the latent trait. For the 1500h and 2000h samples, however, the corresponding proportions of variances amounted only to 33% and 28%, respectively. These results appear to reflect the absence of a clear-cut circadian rhythm in some of the women on the second day after delivery.