Estimation of Standardized Mortality Ratio in Epidemiological Studies

In presenting this thesis in partial fiilfillment of the requirements for an advanced degree at The University of Maine, I agree that the Library shall make it freely available for inspection. I hrther agree that permission for "fair use" copying of this thesis for scholarly purposes may be granted by the Librarian. It is understood that any copying or publication of this thesis for financial gain shall not be allowed without my written permission. In epidemiological studies, we are often interested in comparing the mortality rate of a certain cohort to that of a standard population. A standard computational statistic in this regard is the Standardized Mortality Ratio (SMR) @reslow and Day, 1987), given by where 0 is the number of deaths observed in the study cohort from a specified cause, E is the expected number calculated from that population. In occupational epidemiology, the SMR is the most common measure of risk. It is a comparative statistic. It is frequently based on a comparison of the number0 in the cohort with the expected value E in a standard population. Our goal is to estimate the value of SMR. Since the expected value E is assumed to be fixed for a certain standard population, what we need to do is to estimate the observed number 0 , which is-. traditionally assumed to be Poisson distributed. We are primarily interested in confidence limits for the Poisson parameter. Many authors have discussed methods for constructing confidence intervals for the Sh4R. These confidence intervals amount to obtaining more accurate confidence intervals for the Poisson parameter. In this thesis, by using classic normal approximations, exact confidence intervals based on the chi-square distribution, binomial approximations and shortcut methods, we investigate more accurate methods for the statistical analysis of Poisson distributed data and carry out some simulation studies in order to obtain and compare better estimates of the Sh4R. These methods will be employed to develop an improved analysis of the Sh4R with missing death certificates. ACKNOWLEDGEMENTS I am grateful to express deep gratitude to Professor Ramesh C. Gupta for his invaluable advice and help at every stage of my graduate study. I also thank my other committee members, Professor Pushpa L. Gupta and Professor David M. Bradley for their help and participation. In particular, I thank all my committee members for their help and encouragement, not only in completing this thesis, but also in my pursuit …