Electronic Thesis and Dissertation Repository


Master of Science


Epidemiology and Biostatistics


Dr. Neil Klar

2nd Supervisor

Dr. Guangyong Zou

Joint Supervisor


For many-to-one comparisons of independent binomial proportions using their ratios, we propose the MOVER approach generalizing Fieller's theorem to a ratio of proportions by obtaining variance estimates in the neighbourhood of confidence limits for each proportion. We review two existing methods of inverting Wald and score test statistics and compare their performance with the proposed MOVER approach with score limits and Jeffreys limits for single proportions. As an appropriate multiplicity adjustment incorporating correlations between risk ratios, a Dunnett critical value is computed assuming a common, constant correlation of 0.5 instead of plugging in sample correlation coefficients. The simulation results suggest that the MOVER approach has desirable operating characteristics comparable to those of the method of inverting score test statistics. The MOVER with Jeffreys limits yields the median joint coverage percentage closest to the nominal level but its intervals may be wider than the other intervals in some parameter settings.

main(finalsubmission).pdf (542 kB)
final submission

Included in

Biostatistics Commons