Intraclass Correlation Coefficients for Designing Cluster-Randomized Trials in Sub-Saharan Africa Education. (December 2016)

• Record Type: Journal Article
• Authors: Kelcey, Ben; Shen, Zuchao; Spybrook, Jessaca
• Other Names: Kelcey Ben guest-editor.; Spybrook Jessaca guest-editor.
• Is Part Of: Evaluation review. Volume 40:Number 6(2016)
• Page Start: 500
• Page End: 525
• Publication Date: 2016-12
• Subjects: education -- content area -- program design and development -- design and evaluation of programs and policies -- outcome evaluation (other than economic evaluation); Evaluation research (Social action programs) -- Periodicals; 361.0072
• DOI: 10.1177/0193841X16660246
• Languages: English
• ISSNs: 0193-841X

Abstract

Objective: Over the past two decades, the lack of reliable empirical evidence concerning the effectiveness of educational interventions has motivated a new wave of research in education in sub-Saharan Africa (and across most of the world) that focuses on impact evaluation through rigorous research designs such as experiments. Often these experiments draw on the random assignment of entire clusters, such as schools, to accommodate the multilevel structure of schooling and the theory of action underlying many school-based interventions. Planning effective and efficient school randomized studies, however, requires plausible values of the intraclass correlation coefficient (ICC) and the variance explained by covariates during the design stage. The purpose of this study was to improve the planning of two-level school-randomized studies in sub-Saharan Africa by providing empirical estimates of the ICC and the variance explained by covariates for education outcomes in 15 countries. Method: Our investigation drew on large-scale representative samples of sixth-grade students in 15 countries in sub-Saharan Africa and includes over 60, 000 students across 2, 500 schools. We examined two core education outcomes: standardized achievement in reading and mathematics. We estimated a series of two-level hierarchical linear models with students nested within schools to inform the design of two-level school-randomized trials. Results: The analyses suggested that outcomes were substantially clustered within schools but that the magnitude of the clustering varied considerably across countries. Similarly, the results indicated that covariance adjustment generally reduced clustering but that the prognostic value of such adjustment varied across countries.