The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models

Kerkhoff D, Nussbeck FW. The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models. Frontiers in Psychology. 2019;10: 1067.In educational psychology, observational units are oftentimes nested within superordinate groups. Researchers need to account for hierarchy in the data by means of multilevel modeling, but especially in three-level longitudinal models, it is often unclear which sample size is necessary for reliable parameter estimation. To address this question, we generated a population dataset based on a study in the field of educational psychology, consisting of 3000 classrooms (level-3) with 55000 students (level-2) measured at 5 occasions (level-1), including predictors on each level and interaction effects. Drawing from this data, we realized 1000 random samples each for various sample and missing value conditions and compared analysis results with the true population parameters. We found that sampling at least 15 level-2 units each in 35 level-3 units results in unbiased fixed effects estimates, whereas higher-level random effects variance estimates require larger samples. Overall, increasing the level-2 sample size most strongly improves estimation soundness. We further discuss how data characteristics influence parameter estimation and provide specific sample size recommendations

The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models

In educational psychology, observational units are oftentimes nested within superordinate groups. Researchers need to account for hierarchy in the data by means of multilevel modeling, but especially in three-level longitudinal models, it is often unclear which sample size is necessary for reliable parameter estimation. To address this question, we generated a population dataset based on a study in the field of educational psychology, consisting of 3000 classrooms (level-3) with 55000 students (level-2) measured at 5 occasions (level-1), including predictors on each level and interaction effects. Drawing from this data, we realized 1000 random samples each for various sample and missing value conditions and compared analysis results with the true population parameters. We found that sampling at least 15 level-2 units each in 35 level-3 units results in unbiased fixed effects estimates, whereas higher-level random effects variance estimates require larger samples. Overall, increasing the level-2 sample size most strongly improves estimation soundness. We further discuss how data characteristics influence parameter estimation and provide specific sample size recommendations

Multimethod latent class analysis

Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model

Multimethod latent class analysis

Nussbeck FW, Eid M. Multimethod latent class analysis. Frontiers in Psychology. 2015;6: 1332.Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model

Infatuation and Lovesickness on Sleep Quality and Dreams in Adolescence

Schlarb A, Brock N, Nussbeck FW, Claßen M. Infatuation and Lovesickness on Sleep Quality and Dreams in Adolescence. Health. 2017;9(01):138-152.Background: Infatuation and lovesickness are widespread and significant experiences in adolescence. Less is known about the connection between infatuation/lovesickness and sleep. The few studies, examining the link between infatuation and sleep quality show inconsistent results. The link between lovesickness and sleep as well as the link between infatuation/lovesickness and dreams has not been investigated yet. The aim of this study was to examine whether infatuation and lovesickness are linked to sleep quality and dreams in adolescents. Methods: A self-assessment online questionnaire was constructed to assess adolescents’ infatuation, lovesickness, sleep quality and dreams. In total, data of 630 adolescents and young adults (150 males, 480 females; aged 16 - 21) were analyzed in this study. Results: Infatuation did not relate to overall sleep quality and dreams. Sleep disturbances, as a component of overall sleep quality, were more frequent in infatuated adolescents. Adolescents currently suffering from lovesickness reported a significantly lower sleep quality, more negative dreams and nightmares. Furthermore, nightmares influenced them more strongly the next day. Conclusions: The associations between infatuation/lovesickness and sleep provide evidence for the far reaching effects of infatuation and lovesickness in adolescents’ lives. The fact that lovesickness leads to lower sleep quality and more negative dreams should be integrated in new approaches of insomnia treatment

The efficacy of an educational program for parents of children with epilepsy (FAMOSES): Results of a controlled multicenter evaluation study

Hagemann A, Pfäfflin M, Nussbeck FW, May T. The efficacy of an educational program for parents of children with epilepsy (FAMOSES): Results of a controlled multicenter evaluation study. Epilepsy & Behavior. 2016;64(Part A):143-151

Analyzing Dyadic Sequence Data—Research Questions and Implied Statistical Models

Fuchs P, Nussbeck FW, Meuwly N, Bodenmann G. Analyzing Dyadic Sequence Data—Research Questions and Implied Statistical Models. Frontiers in Psychology. 2017;8: 429.The analysis of observational data is often seen as a key approach to understanding dynamics in romantic relationships but also in dyadic systems in general. Statistical models for the analysis of dyadic observational data are not commonly known or applied. In this contribution, selected approaches to dyadic sequence data will be presented with a focus on models that can be applied when sample sizes are of medium size (N = 100 couples or less). Each of the statistical models is motivated by an underlying potential research question, the most important model results are presented and linked to the research question. The following research questions and models are compared with respect to their applicability using a hands on approach: (I) Is there an association between a particular behavior by one and the reaction by the other partner? (Pearson Correlation); (II) Does the behavior of one member trigger an immediate reaction by the other? (aggregated logit models; multi-level approach; basic Markov model); (III) Is there an underlying dyadic process, which might account for the observed behavior? (hidden Markov model); and (IV) Are there latent groups of dyads, which might account for observing different reaction patterns? (mixture Markov; optimal matching). Finally, recommendations for researchers to choose among the different models, issues of data handling, and advises to apply the statistical models in empirical research properly are given (e.g., in a new r-package “DySeq”)

Cognitive change predicts symptom reduction with cognitive therapy for posttraumatic stress disorder

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

Coordination and communication in healthcare action teams

Communication and coordination represent central processes in healthcare action teams. However, we have a limited understanding of how expertise affects these processes and to what extent these effects are shaped by interprofessional differences. The current study addresses these questions by jointly investigating the influence of different aspects of expertise – individual expertise, team familiarity, and expertise asymmetry – on coordination quality and communication openness. We tested our propositions in two hospitals: one in Switzerland (CH, Sample 1) and one in the United Kingdom (UK, Sample 2). Both samples included two-person anesthesia action teams consisting of a physician and a nurse (N/CH = 47 teams, N/UK = 48 teams). We used a correlational design with two measurement points (i.e., pre- and postoperation). To consider potential interprofessional differences, we analyzed our data with actor-partner interdependence models. Moreover, we explored differences in the effects of expertise between both hospitals. Our findings suggest that nurses’ expertise is the most important predictor of coordination quality and communication openness. Overall, differences between the two hospitals were more prevalent than interprofessional differences between physicians and nurses. The current study provides a nuanced picture of the effects of expertise, and thereby extends our understanding of interprofessional teamwork