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A Note on Interval Estimation of the Simple Difference in Data with Correlated Matched Pairs
Author(s) -
Lui KungJong
Publication year - 2001
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200105)43:2<235::aid-bimj235>3.0.co;2-d
Subject(s) - estimator , mathematics , statistics , intraclass correlation , independence (probability theory) , interval estimation , interval (graph theory) , cluster sampling , simple (philosophy) , correlation , sample size determination , cluster (spacecraft) , monte carlo method , confidence interval , sampling (signal processing) , combinatorics , computer science , population , philosophy , demography , geometry , epistemology , filter (signal processing) , sociology , computer vision , programming language , psychometrics
When we employ cluster sampling to collect data with matched pairs, the assumption of independence between all matched pairs is not likely true. This paper notes that applying interval estimators, that do not account for the intraclass correlation between matched pairs, to estimate the simple difference between two proportions of response can be quite misleading, especially when both the number of matched pairs per cluster and the intraclass correlation between matched pairs within clusters are large. This paper develops two asymptotic interval estimators of the simple difference, that accommodate the data of cluster sampling with correlated matched pairs. This paper further applies Monte Carlo simulation to compare the finite sample performance of these estimators and demonstrates that the interval estimator, derived from a quadratic equation proposed here, can actually perform quite well in a variety of situations.