Fundamentals of Hierarchical Linear and Multilevel Modeling

A Cultural-Ecological Model of School Climate

“…Research designs including longitudinal analysis, moderation, mediation, and multilevel modeling are better suited to examine the nested arrangements and the mediating or moderating effects of specific variables (e.g., small class size, gender) on outcomes. Multilevel modeling, such as hierarchical linear modeling (HLM; Garson, 2013) analysis, is a widely supported analytic methodology for ecological models (Bronfenbrenner & Morris, 2006;Tudge et al, 2009). Multilevel modeling is equipped to test multiple theories while simultaneously examining variables across levels (e.g., individuals, families, schools) to examine crosslevel causal effects (Garson, 2013).…”

“…Multilevel modeling, such as hierarchical linear modeling (HLM; Garson, 2013) analysis, is a widely supported analytic methodology for ecological models (Bronfenbrenner & Morris, 2006;Tudge et al, 2009). Multilevel modeling is equipped to test multiple theories while simultaneously examining variables across levels (e.g., individuals, families, schools) to examine crosslevel causal effects (Garson, 2013). Bronfenbrenner (2005) also suggested the use of research designs that are considered to be generative and focused on a deeper understanding of individuals and cultural contexts to generate ideas about the processes that affect individual development.…”

The Nature of the Association between Anxiety Sensitivity and Pain-Related Anxiety: Evidence from Correlational and Intervention Studies

“…We investigated treatment outcome for AS and pain-related anxiety using multilevel modelling with HLM 7.0 software. This approach accounts for repeated measures (Garson, 2013) and takes a maximum likelihood approach to missing data (Graham, 2009). We estimated a separate model -a twolevel model with repeated measures (level 1) nested within participants (level 2) -for each of the pain-related anxiety outcome variables using restricted maximum likelihood estimation.…”

Auf die Größe kommt es an! Neue empirische Evidenz zur Wahlbeteiligung in Gemeinden

“…Die Anwendung eines hierarchischen, gemischten Modells auf das vorliegende Datenset könnte zu verzerrten Schätzungen führen. Garson (2013) Snijders und Bosker (1999), Radenbusch und Bryk (2002) oder Hox (2010) verweisen, wird -hier in der Anwendung eines Cross-Classified-Modells -folgender "Fahrplan der Mehrebenanalyse" eingehalten: In einem ersten Arbeitsschritt wird über die Schätzung eines Random-Intercept(s)-Only-Modells (RIO) die Kontextabhängigkeit der abhängigen Variable "Wahlbeteiligung bei Gemeindewahlen (VT)" dargestellt (Langer 2010, S. 745 ff.). Dieses erste Modell, auch "Empty Model" genannt, bietet Einblick in die Varianzaufteilung zwischen den Ebenen und Kontexten.…”