Dein Suchergebnis zum Thema: Olive

Missing data are a common challenge in multilevel designs, and multiple imputation (MI) is often used for handling them. Past research has shown that multilevel MI provides an effective treatment of missing data, so long as the imputation model takes the multilevel structure and the intended analyses into account, and modern methods have been developed that can accommodate even complex types of analyses. However, multilevel MI can be difficult to apply in practice, where the multilevel structure is often not very pronounced or not of immediate interest in the analysis. In these applications, existing methods can become unstable and often struggle to provide reliable results. In this article, we introduce a fully conditional specification (FCS) approach to multilevel MI that combines single-level imputation methods with group means (GM) or adjusted group means (AGM) to accommodate the multilevel structure. Based on theoretical investigations and multiple simulation studies, we evaluated the performance of these methods across balanced and unbalanced designs and with larger numbers of variables. Our findings suggest that the AGM approach – though not the GM approach – performs well across most scenarios we investigated and can even outperform conventional multilevel MI approaches in challenging applications. We also provide an illustrative example of implementing these methods in a simulated setting and discuss the implications of our findings for practice.
Fachzeitschrift › Forschung › begutachtet Publikationsdaten Von Simon Grund, Oliver

While emerging evidence links peer group composition to children’s language development, most studies are limited to short-term effects and rarely examine potential long-term patterns across educational stages in which children encounter different peer groups. This study examined whether the average language skills of preschool peers showed a lasting association with children’s receptive vocabulary in third grade, and further explored whether subsequent primary school peer groups added to or moderated this association. Using data from the German National Educational Panel Study (NEPS; n = 499 target children in 213 preschool groups and 190 primary school classrooms), we applied multilevel regression analyses accounting for children’s baseline vocabulary, sociodemographic characteristics, and the nested structure of the data. Preschool peer language skills showed a modest positive association with later vocabulary, which was moderated by primary school peer group skills. Contrary to expectations, preschool effects were strongest when children entered lower-skilled primary school peer groups and were not detectable in higher-skilled groups. No independent additive effect of primary school peer skills emerged. These findings suggest that preschool peer groups may serve as a compensatory foundation when later peer environments are less supportive and underscore the importance of considering consecutive peer contexts when examining longer-term associations in language development.
Fachzeitschrift › Forschung › begutachtet Publikationsdaten Von Franziska Hürlimann, Oliver

In longitudinal assessments, tests are frequently used to estimate trends over time. However, when item parameters lack invariance, time-point comparisons can be distorted, necessitating appropriate statistical methods to achieve accurate estimation. This study compares trend estimates using the two-parameter logistic (2PL) model under item parameter drift (IPD) across five trend-estimation approaches for two time points: First, concurrent calibration, which jointly estimates item parameters across multiple time points. Second, fixed calibration, which estimates item parameters at a single time point and fixes them at the other time point. Third, robust linking with Haberman and Haebara as linking methods withLporL0losses. Fourth, non-invariant items are detected using likelihood-ratio tests or the root mean square deviation statistic with fixed or data-driven cutoffs, and trend estimates are then recomputed using only the detected invariant items under partial invariance. Fifth, regularized estimation under a smooth Bayesian information criterion (SBIC) is applied, shrinking small or null IPD effects toward zero while estimating all others as nonzero. Bias and relative root mean square error (RMSE) were evaluated for the mean and SD at T2. An empirical example using synthetic longitudinal reading data, applying the trend-estimation approaches, is provided. The results indicate that the regularized estimation with SBIC performed best across conditions, maintaining low bias and RMSE, followed by robust linking methods. Specifically, Haberman linking with theL0loss function showed superior performance under unbalanced IPD, outperforming the partial invariance approaches. Concurrent and fixed calibration showed the poorest trend recovery under unbalanced IPD conditions.
Fachzeitschrift › Forschung › begutachtet Publikationsdaten Von Oskar Engels, Oliver

In longitudinal assessments, tests are frequently used to estimate trends over time. However, when item parameters lack invariance, time-point comparisons can be distorted, necessitating appropriate statistical methods to achieve accurate estimation. This study compares trend estimates using the two-parameter logistic (2PL) model under item parameter drift (IPD) across five trend-estimation approaches for two time points: First, concurrent calibration, which jointly estimates item parameters across multiple time points. Second, fixed calibration, which estimates item parameters at a single time point and fixes them at the other time point. Third, robust linking with Haberman and Haebara as linking methods withLporL0losses. Fourth, non-invariant items are detected using likelihood-ratio tests or the root mean square deviation statistic with fixed or data-driven cutoffs, and trend estimates are then recomputed using only the detected invariant items under partial invariance. Fifth, regularized estimation under a smooth Bayesian information criterion (SBIC) is applied, shrinking small or null IPD effects toward zero while estimating all others as nonzero. Bias and relative root mean square error (RMSE) were evaluated for the mean and SD at T2. An empirical example using synthetic longitudinal reading data, applying the trend-estimation approaches, is provided. The results indicate that the regularized estimation with SBIC performed best across conditions, maintaining low bias and RMSE, followed by robust linking methods. Specifically, Haberman linking with theL0loss function showed superior performance under unbalanced IPD, outperforming the partial invariance approaches. Concurrent and fixed calibration showed the poorest trend recovery under unbalanced IPD conditions.
Fachzeitschrift › Forschung › begutachtet Publikationsdaten Von Oskar Engels, Oliver

While emerging evidence links peer group composition to children’s language development, most studies are limited to short-term effects and rarely examine potential long-term patterns across educational stages in which children encounter different peer groups. This study examined whether the average language skills of preschool peers showed a lasting association with children’s receptive vocabulary in third grade, and further explored whether subsequent primary school peer groups added to or moderated this association. Using data from the German National Educational Panel Study (NEPS; n = 499 target children in 213 preschool groups and 190 primary school classrooms), we applied multilevel regression analyses accounting for children’s baseline vocabulary, sociodemographic characteristics, and the nested structure of the data. Preschool peer language skills showed a modest positive association with later vocabulary, which was moderated by primary school peer group skills. Contrary to expectations, preschool effects were strongest when children entered lower-skilled primary school peer groups and were not detectable in higher-skilled groups. No independent additive effect of primary school peer skills emerged. These findings suggest that preschool peer groups may serve as a compensatory foundation when later peer environments are less supportive and underscore the importance of considering consecutive peer contexts when examining longer-term associations in language development.
Fachzeitschrift › Forschung › begutachtet Publikationsdaten Von Franziska Hürlimann, Oliver

Background Anxiety disorders are prevalent and associated with substantial distress and impairment. Within the metacognitive model of emotional disorders, the cognitive attentional syndrome (CAS) and associated metacognitions maintain anxiety. The Attention Training Technique (ATT) targets the CAS and related metacognitions. However, less is known about how symptoms and metacognitive mechanisms evolve across treatment phases. Objective The study aimed to explore temporal dynamics in emotional symptoms and metacognitive mechanisms during group ATT by estimating mean levels, variability, and coupling across the pre-, during-, and post-treatment phases using ecological momentary assessment (EMA). Method Nineteen young adults with social anxiety disorder, panic disorder with agoraphobia, or generalized anxiety disorder participated. EMA was completed four times daily over six weeks: two weeks before treatment, two weeks during treatment, and two weeks after treatment. Each assessment included ten items measuring emotional symptoms (e.g., nervousness) and metacognitive mechanisms (e.g., worry, uncontrollability). Results Three patterns of change emerged: (1) reduced mean levels without change in variability (nervousness, self-consciousness, and worry); (2) reduced mean levels and reduced variability (threat monitoring); and (3) reduced mean levels and reduced variability during treatment, followed by an increase in variability after treatment (uncontrollability, difficulty collecting thoughts, and meta-worry). Conclusions The findings provide new insights into dynamic patterns of change in symptoms and metacognitive mechanisms before, during, and after ATT. Patterns of change in both intensity and stability may be relevant for understanding treatment response and vulnerability following treatment, suggesting the potential clinical relevance of monitoring these mechanisms.
Ebrahimi, Oliver Lüdtke, Steffen Nestler, Sverre Urnes Johnson Originalsprache Englisch

Background Anxiety disorders are prevalent and associated with substantial distress and impairment. Within the metacognitive model of emotional disorders, the cognitive attentional syndrome (CAS) and associated metacognitions maintain anxiety. The Attention Training Technique (ATT) targets the CAS and related metacognitions. However, less is known about how symptoms and metacognitive mechanisms evolve across treatment phases. Objective The study aimed to explore temporal dynamics in emotional symptoms and metacognitive mechanisms during group ATT by estimating mean levels, variability, and coupling across the pre-, during-, and post-treatment phases using ecological momentary assessment (EMA). Method Nineteen young adults with social anxiety disorder, panic disorder with agoraphobia, or generalized anxiety disorder participated. EMA was completed four times daily over six weeks: two weeks before treatment, two weeks during treatment, and two weeks after treatment. Each assessment included ten items measuring emotional symptoms (e.g., nervousness) and metacognitive mechanisms (e.g., worry, uncontrollability). Results Three patterns of change emerged: (1) reduced mean levels without change in variability (nervousness, self-consciousness, and worry); (2) reduced mean levels and reduced variability (threat monitoring); and (3) reduced mean levels and reduced variability during treatment, followed by an increase in variability after treatment (uncontrollability, difficulty collecting thoughts, and meta-worry). Conclusions The findings provide new insights into dynamic patterns of change in symptoms and metacognitive mechanisms before, during, and after ATT. Patterns of change in both intensity and stability may be relevant for understanding treatment response and vulnerability following treatment, suggesting the potential clinical relevance of monitoring these mechanisms.
Ebrahimi, Oliver Lüdtke, Steffen Nestler, Sverre Urnes Johnson Originalsprache Englisch

Nach einer spannenden Auswahlrunde steht das deutsche Nationalteam für die European Olympiad of Experimental Science 2024 (EOES) fest. 
Brandenburg)  Vinzent Schultze (Chemie, Max-Steenbeck-Gymnasium, Cottbus, Brandenburg)  Oliver

Deutsches Schülerteam gewinnt 2x Bronze, 3x Silber und 1x Gold bei der 20th International Junior Science Olympiad in Bangkok.
Maria Anna Salsa und Benjamin Krüger aus München, Jakob Sierpinski aus Leipzig und Oliver

Pädagogisch-Psychologische Methoden und Daten-Wissenschaften Der Direktor von dieser Abteilung heißt Oliver