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Meta‐analysis using multilevel models with an application to the study of class size effects
Author(s) -
Goldstein Harvey,
Yang Min,
Omar Rumana,
Turner Rebecca,
Thompson Simon
Publication year - 2000
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/1467-9876.00200
Subject(s) - multilevel model , respondent , hierarchy , aggregate (composite) , class size , class (philosophy) , aggregate data , statistics , hierarchical database model , meta analysis , mathematics , econometrics , computer science , mathematics education , data mining , artificial intelligence , medicine , materials science , political science , economics , law , market economy , composite material
Meta‐analysis is formulated as a special case of a multilevel (hierarchical data) model in which the highest level is that of the study and the lowest level that of an observation on an individual respondent. Studies can be combined within a single model where the responses occur at different levels of the data hierarchy and efficient estimates are obtained. An example is given from studies of class sizes and achievement in schools, where study data are available at the aggregate level in terms of overall mean values for classes of different sizes, and also at the student level.