Abstract
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about multilevel effect size have been rare and those that have recently appeared had an emphasis on strictly hierarchical data structure. This article extends the work on multilevel standardized mean differences from strictly hierarchical structure to both fully and partially cross-classified structures. Analytically derived formulae for calculating effect sizes and the corresponding sampling variances (or standard errors) are presented, verified by simulation results, and illustrated with real data examples. Implications for primary research studies and meta-analyses are discussed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
