Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literature, but there is significant variability in the current approaches to the conducting and reporting of HLM. The field currently lacks a general consensus around important issues such as the number of levels of analysis that are important to include and how much variance should be accounted for at each level in order for the HLM analysis to have practical significance (Dedrick et al., Rev Educ Res 79:69–102, 2009). The purpose of this research is to explore the use of a 3-level HLM model, appropriate contextualizing of results of HLM, and the interpretation of HLM results that resonates with practice. We used an example of a 3-level model from t...
The utility of hierarchical linear modeling (HLM) in the analysis of nested data is well established...
Because public schools do not randomly assign students and teachers across schools (methodological u...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
How college affects students is a central phenomenon of interest in higher education research. Howev...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
When students are nested within course sections, the assumption of independence of residuals is unli...
This study examined the reporting practices used by higher education scholars to communicate the met...
Increasingly, researchers are faced with nested and cross‐level data. For example, students are clus...
The purpose of this article is to provide higher education researchers with an illustrative example ...
In most multi-campus studies of college impact that have been conducted over the past four decades, ...
In most multi-campus studies of college impact that have been conducted over the past four decades, ...
The utility of hierarchical linear modeling (HLM) in the analysis of nested data is well established...
Because public schools do not randomly assign students and teachers across schools (methodological u...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
How college affects students is a central phenomenon of interest in higher education research. Howev...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
When students are nested within course sections, the assumption of independence of residuals is unli...
This study examined the reporting practices used by higher education scholars to communicate the met...
Increasingly, researchers are faced with nested and cross‐level data. For example, students are clus...
The purpose of this article is to provide higher education researchers with an illustrative example ...
In most multi-campus studies of college impact that have been conducted over the past four decades, ...
In most multi-campus studies of college impact that have been conducted over the past four decades, ...
The utility of hierarchical linear modeling (HLM) in the analysis of nested data is well established...
Because public schools do not randomly assign students and teachers across schools (methodological u...
Abstract Previous publications on hierarchical linear modeling (HLM) have provided guidance on how ...