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Interval estimation and hypothesis testing of intraclass correlation coefficients: the generalized variable approach
Author(s) -
Tian Lili
Publication year - 2005
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.2026
Subject(s) - intraclass correlation , confidence interval , statistics , interval estimation , mathematics , inference , correlation , type i and type ii errors , interval (graph theory) , variable (mathematics) , statistical hypothesis testing , fisher transformation , correlation coefficient , computer science , artificial intelligence , combinatorics , mathematical analysis , geometry , psychometrics
In this paper, we propose a novel approach using the concept of generalized variable (GV) for the confidence interval estimation of the difference of two intraclass correlation coefficients under unequal family sizes. This approach can also easily provide P ‐values for hypothesis testing. Simulation results show that the GV approach can provide confidence intervals with good coverage properties and perform hypothesis testing with satisfactory type‐I error control. Furthermore, the confidence intervals and P ‐values by GV approach can be easily obtained by simulation. Therefore the GV approach is a suitable candidate for making inference concerning two intraclass correlation coefficients. Copyright © 2004 John Wiley & Sons, Ltd.