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Intraclass correlation coefficients and bootstrap methods of hierarchical binary outcomes
Author(s) -
Ren Shiquan,
Yang Shuqin,
Lai Shenghan
Publication year - 2006
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2457
Subject(s) - intraclass correlation , statistics , binary number , correlation , mathematics , computer science , reproducibility , geometry , arithmetic
Intraclass correlation coefficients are designed to assess consistency or conformity between two or more quantitative measurements. When multistage cluster sampling is implemented, no methods are readily available to estimate intraclass correlations of binomial‐distributed outcomes within a cluster. Because statistical distribution of the intraclass correlation coefficients could be complicated or unspecified, we propose using a bootstrap method to estimate the standard error and confidence interval within the framework of a multilevel generalized linear model. We compared the results derived from a parametric bootstrap method with those from a non‐parametric bootstrap method and found that the non‐parametric method is more robust. For non‐parametric bootstrap sampling, we showed that the effectiveness of sampling on the highest level is greater than that on lower levels; to illustrate the effectiveness, we analyse survey data in China and do simulation studies. Copyright © 2006 John Wiley & Sons, Ltd.