A Novel Bootstrap Procedure for Assessing the Relationship between Class Size and Achievement

DOI10.1111/1467-9876.00415zbMath1111.62378OpenAlexW2149695156WikidataQ58618870 ScholiaQ58618870MaRDI QIDQ76346

James R. Carpenter, Harvey Goldstein, Jon Rasbash, James Carpenter, Harvey Goldstein, Jon Rasbash

Publication date: 23 September 2003

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00415

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Nonparametric statistical resampling methods (62G09) Applications of statistics to psychology (62P15)

Related Items (8)

Bootstrapped inference for variance parameters, measures of heterogeneity and random effects in multilevel logistic regression models ⋮ Value added in hierarchical linear mixed models with error in variables ⋮ Smoothing and Benchmarking for Small Area Estimation ⋮ An Efficient Morris Method-Based Framework for Simulation Factor Screening ⋮ lmeresampler ⋮ Bootstrap estimation of uncertainty in prediction for generalized linear mixed models ⋮ The Wild Bootstrap for Multilevel Models ⋮ Bootstrapping data with multiple levels of variation

Uses Software

• MLwiN

Cites Work

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• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• Bootstrap: more than a stab in the dark? With discussion and a rejoinder by the author
• Bootstrap confidence intervals. With comments and a rejoinder by the authors
• Multilevel mixed linear model analysis using iterative generalized least squares
• Restricted unbiased iterative generalized least-squares estimation
• Consistency of the bootstrap procedure in individual bioequivalence

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