The purpose of this article is to provide higher education researchers with an illustrative example of meta-analysis utilizing hierarchical linear modeling (HLM). This article demonstrates the step-by-step process of meta-analysis using a recently-published study examining the effects of curricular and co-curricular diversity activities on racial bias in college students as an example (Denson, Rev Educ Res 79:805-838, 2009). The authors present an overview of the meta-analytic approach and describe a meta-analysis from beginning to end. The example includes: problem specification; research questions; study retrieval and selection; coding procedure; calculating effect sizes; visual displays and summary statistics; conducting HLM analyses; an...
The early and recent history of meta-analysis is outlined. After providing a definition of meta-anal...
How college affects students is a central phenomenon of interest in higher education research. Howev...
Increasingly, researchers are faced with nested and cross‐level data. For example, students are clus...
Meta-analysis is a valuable statistical technique for synthesising the available educational researc...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
The objectives of the present mixed-effects meta-analytic application are to provide practical guide...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
When students are nested within course sections, the assumption of independence of residuals is unli...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
This study examined the reporting practices used by higher education scholars to communicate the met...
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...
Accessed 63,460 times on https://pareonline.net from November 13, 1999 to December 31, 2019. For dow...
The need for comprehensive and systematic research syntheses has been increasing as the number of pr...
Keeping up with the literature of education becomes a more difficult task each year. The Current Ind...
The early and recent history of meta-analysis is outlined. After providing a definition of meta-anal...
How college affects students is a central phenomenon of interest in higher education research. Howev...
Increasingly, researchers are faced with nested and cross‐level data. For example, students are clus...
Meta-analysis is a valuable statistical technique for synthesising the available educational researc...
Hierarchical linear modeling (HLM) has become increasingly popular in the higher education literatur...
The objectives of the present mixed-effects meta-analytic application are to provide practical guide...
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is p...
When students are nested within course sections, the assumption of independence of residuals is unli...
In social research work, the structure of the data are often hierarchical. Hierarchical linear model...
This study examined the reporting practices used by higher education scholars to communicate the met...
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...
Accessed 63,460 times on https://pareonline.net from November 13, 1999 to December 31, 2019. For dow...
The need for comprehensive and systematic research syntheses has been increasing as the number of pr...
Keeping up with the literature of education becomes a more difficult task each year. The Current Ind...
The early and recent history of meta-analysis is outlined. After providing a definition of meta-anal...
How college affects students is a central phenomenon of interest in higher education research. Howev...
Increasingly, researchers are faced with nested and cross‐level data. For example, students are clus...