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The present contribution provides a tutorial for the estimation of the social relations model (SRM) by means of structural equation modeling (SEM). In the overarching SEM-framework, the SRM without roles (with interchangeable dyads) is derived as a more restrictive form of the SRM with roles (with noninterchangeable dyads). Starting with the simplest type of the SRM for one latent construct assessed by one manifest round-robin indicator, we show how the model can be extended to multiple constructs each measured by multiple indicators. We illustrate a multiple constructs multiple indicators SEM SRM both with and without roles with simulated data and explain the parameter interpretations. We present how testing the substantial model assumptions can be disentangled from testing the interchangeability of dyads. Additionally, we point out modeling strategies that adhere to cases in which only some members of a group can be differentiated with regards to their roles (i.e., only some group members are noninterchangeable). In the online supplemental materials , we provide concrete examples of specific modeling problems and their implementation into statistical software (Mplus, lavaan, and OpenMx). Advantages, caveats, possible extensions, and limitations in comparison with alternative modeling options are discussed. The present contribution provides a tutorial for the estimation of the social relations model (SRM) by means of structural equation modeling (SEM). In the overarching SEM-framework, the SRM without roles (with interchangeable dyads) is derived as a more restrictive form of the SRM with roles (with noninterchangeable dyads). Starting with the simplest type of the SRM for one latent construct assessed by one manifest round-robin indicator, we show how the model can be extended to multiple constructs each measured by multiple indicators. We illustrate a multiple constructs multiple indicators SEM SRM both with and without roles with simulated data and explain the parameter interpretations. We present how testing the substantial model assumptions can be disentangled from testing the interchangeability of dyads. Additionally, we point out modeling strategies that adhere to cases in which only some members of a group can be differentiated with regards to their roles (i.e., only some group members are noninterchangeable). In the online supplemental materials , we provide concrete examples of specific modeling problems and their implementation into statistical software (Mplus, lavaan, and OpenMx). Advantages, caveats, possible extensions, and limitations in comparison to alternative modeling options are discussed. [ABSTRACT FROM AUTHOR]

Latent state-trait (LST) models are increasingly applied in psychology. Although existing LST models offer many possibilities for analyzing variability and change, they do not allow researchers to relate time-varying or time-invariant covariates, or a combination of both, to loading, intercept, and factor variance parameters in LST models. We present a general framework for the inclusion of nominal and/or continuous time-varying and time-invariant covariates in LST models. The new framework builds on modern LST theory and Bayesian moderated nonlinear factor analysis and is termed moderated nonlinear LST (MN-LST) framework. The MN-LST framework offers new modeling possibilities and allows for a fine-grained analysis of trait change, person-by-situation interaction effects, as well as inter- or intraindividual variability. The new MN-LST approach is compared to alternative modeling strategies. The advantages of the MN-LST approach are illustrated in an empirical application examining dyadic coping in romantic relationships. Finally, the advantages and limitations of the approach are discussed, and practical recommendations are provided. [ABSTRACT FROM AUTHOR]

Purpose: Depressive and anxiety disorders are frequent among people with epilepsies. There are, however, only few longitudinal studies, which examine the relationship between these comorbid psychiatric disorders and epilepsy-related variables. Thus, we investigated the interrelationships of depression and anxiety symptoms with seizure frequency across time.Methods: Before admittance to an epilepsy center (T1) and six months after discharge (T2), patients (n=198) with mainly difficult-to-treat epilepsies completed the Hospital Anxiety and Depression Scale (HADS). Correlation and path analyses were conducted.Results: Depression and anxiety symptoms (HADS) as well as seizure frequency significantly decreased from baseline to follow-up. Both at T1 and T2, seizure frequency was slightly, but significantly correlated with depression and anxiety levels (rs=0.17-.32). Cross-lagged-analyses showed that baseline (T1) level of depression significantly predicted frequency of seizures at follow-up (T2). However, anxiety at T1 was not a significant predictor of seizure frequency at T2 and seizure frequency at T1 did not predict either depressive or anxiety symptoms at T2.Conclusion: The present findings emphasize the importance of psychiatric comorbidities, especially depression, for seizure frequency and its progress in patients with difficult-to-treat epilepsies referred to a specialized epilepsy center. Thus, comorbid psychiatric disorders need specific consideration as part of a comprehensive diagnostic and therapeutic treatment approach. [ABSTRACT FROM AUTHOR]

Although prevention of relationship distress and dissolution has potential to strengthen the well-being of partners and any children they are raising, dissemination of prevention programs can be limited because couples face many barriers to in-person participation. An alternative strategy, providing couples with an instructional DVD, is tested in the present study, in which 330 Caucasian couples (N = 660 participants; mean age: men 41.4 years, women 40.0 years) were randomly assigned to a DVD group without any further support, a DVD group with technical telephone coaching, or a wait-list control group. Couples completed questionnaires at pretest, posttest, and 3 and 6 months after completion of the intervention. Self-report measures of dyadic coping, communication quality, ineffective arguing, and relationship satisfaction were used to test whether the intervention groups improved in comparison with the control group. Women in both intervention groups increased in dyadic coping, reduced conflict behavior, and were more satisfied with their relationship 6 months after the intervention. Effects for men were mixed. Participants with poorer skills reported stronger improvement. Intimate relationships can, within limits, be positively influenced by a self-directed approach. Effective dissemination of principles underlying successful relationships can be facilitated through the use of emerging low-cost tools and technologies. [ABSTRACT FROM AUTHOR]

Objective: There is a growing body of evidence for the effectiveness of trauma-focused cognitive behavior therapy (TF-CBT) for posttraumatic stress disorder (PTSD), but few studies to date have investigated the mechanisms by which TF-CBT leads to therapeutic change. Models of PTSD suggest that a core treatment mechanism is the change in dysfunctional appraisals of the trauma and its aftermath. If this is the case, then changes in appraisals should predict a change in symptoms. The present study investigated whether cognitive change precedes symptom change in Cognitive Therapy for PTSD, a version of TF-CBT. Method: The study analyzed weekly cognitive and symptom measures from 268 PTSD patients who received a course of Cognitive Therapy for PTSD, using bivariate latent growth modeling. Results: Results showed that (a) dysfunctional trauma-related appraisals and PTSD symptoms both decreased significantly over the course of treatment, (b) changes in appraisals and symptoms were correlated, and (c) weekly change in appraisals significantly predicted subsequent reduction in symptom scores (both corrected for the general decrease over the course of therapy). Changes in PTSD symptom severity did not predict subsequent changes in appraisals. Conclusions: The study provided preliminary evidence for the temporal precedence of a reduction in negative trauma-related appraisals in symptom reduction during trauma-focused CBT for PTSD. This supports the role of change in appraisals as an active therapeutic mechanism. [ABSTRACT FROM AUTHOR]

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In a recent article, A. Maydeu-Olivares and D. L. Coffman (2006) presented a random intercept factor approach for modeling idiosyncratic response styles in questionnaire data and compared this approach with competing confirmatory factor analysis models. Among the competing models was the CT-C(M-1) model (M. Eid, 2000). In an application to the Life Orientation Test (M. F. Scheier & C. S. Carver, 1985), Maydeu-Olivares and Coffman found that results obtained from the CT-C(M-1) model were difficult to interpret. In particular, Maydeu-Olivares and Coffman challenged the asymmetry of the CT-C(M-1) model. In the present article, the authors show that the difficulties faced by Maydeu-Olivares and Coffman rest upon an improper interpretation of the meaning of the latent factors. The authors' aim is to clarify the meaning of the latent variables in the CT-C(M-1) model. The authors explain how to properly interpret the results from this model and introduce an alternative restricted model that is conceptually similar to the CT-C(M-1) model and nested within it. The fit of this model is invariant across different reference methods. Finally, the authors provide guidelines as to which model should be used in which research context. [ABSTRACT FROM AUTHOR]

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with 2 latent classes fits the data well. The larger class (76%) consists of individuals whose mood is highly variable, whose general well-being is comparatively lower, and whose mood variability is influenced by daily hassles and uplifts. The smaller class (24%) represents individuals who are rather stable and happier and whose mood is influenced only by daily uplifts but not by daily hassles. A simulation study on the model without covariates with 5 sets of sample sizes and 5 sets of number of occasions revealed that the appropriateness of the parameter estimates of this model depends on number of observations (the higher the better) and number of occasions (the higher the better). Another simulation study estimated Type I and II errors of the Lo-Mendell-Rubin test. [ABSTRACT FROM AUTHOR]

An overview of several models of confirmatory factor analysis for analyzing multitrait-multimethod (MTMM) data and a discussion of their advantages and limitations are provided. A new class of multi-indicator MTMM models combines several strengths and avoids a number of serious shortcomings inherent in previously developed MTMM models. The new models enable researchers to specify and to test trait-specific-method effects. The trait and method concepts composing these models are explained in detail and are contrasted with those of previously developed MTMM models for multiple indicators. The definitions of the models are explained step by step, and a practical empirical application of the models to the measurement of 3 traits x 3 methods is used to demonstrate their advantages and limitations. [ABSTRACT FROM AUTHOR]