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Modified regression coefficient analysis for repeated binary measurements

Title
Modified regression coefficient analysis for repeated binary measurements
Authors
Ahn, CJung, SHKang, SH
Ewha Authors
강승호
Issue Date
2002
Journal Title
JOURNAL OF APPLIED STATISTICS
ISSN
0266-4763JCR Link
Citation
vol. 29, no. 5, pp. 703 - 710
Publisher
CARFAX PUBLISHING
Indexed
SCIE; SCOPUS WOS
Abstract
Myers & Broyles (2000a, 2000b) illustrate that regression coefficient analysis (RCA) is a viable alternative to a generalized estimating equation (GEE) in the analysis of correlated binomial data. Since the regression coefficients (b(i)'s) may have different precisions, we modify RCA by weighting b(i)'s by the inverses of their variances for statistical optimality. We perform the simulation study to evaluate the performance of RCA, modified RCA and GEE in terms of empirical type I errors and empirical powers of the regression coefficients in repeated binary measurement designs with and without dropouts. Two thousand data sets are generated using autoregressive (AR(1)) and compound symmetry (CS) correlation structures. We compare the type I errors and powers of RCA, modified RCA and GEE for the analysis of repeated binary measurement data as a ected by different dropout mechanisms such as random dropouts and treatment dependent dropouts.
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자연과학대학 > 통계학전공 > Journal papers
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