Graduate Thesis Or Dissertation

 

Classification errors in the analysis of fourfold tables Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/w6634591h

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  • Misclassification introduced by fallible measurements affects the estimate of the proportion in a class as well as the comparison of proportions in different classes. In this thesis the magnitude of effects of misclassification and the importance of misclassification error rates on estimates of proportions and variances of these estimates were examined. Studies on the values of the false negative and false positive rates associated with medical screening were reviewed to determine typical levels of error rates occurring in practice. A lack of a consistent relationship between these rates was found and the common assumption of a small constant error rate in all groups being compared was violated in almost all-studies. An attempt was made to determine how robust the usual statistical procedure for analyzing a given set of data is against these classification errors. The study was carried out for the case of two independent binomial samples (very common in epidemiologic research) with the conditional model (Fisher's exact test) considered in detail under various error rates. Substantial effects of misclassification on the estimation of parameters as well as on hypothesis testing showed the importance of estimating the values of the misclassification rates in a particular study. The randomized response technique was used to estimate error rates and the prevalence rate, π, for a situation where the true classification can only be obtained directly from the respondent, but the response has a stigmatizing nature. An unbiased estimate of π was obtained along with an expression for the variance of π. Formulas for sample size determination for fixed cost and fixed variance problems are given.
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