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Articles 1 - 4 of 4
Full-Text Articles in Clinical Trials
Non-Inferiority Testing: Kernel Estimation And Overlap Measure, Larie C. Ward
Non-Inferiority Testing: Kernel Estimation And Overlap Measure, Larie C. Ward
College of Graduate Studies: Theses & Dissertations
In non-inferiority testing, the decision of whether a proposed treatment is non-inferior to a reference treatment depends on model assumptions and choices of acceptable tolerance limits. Here, we consider a method that employs kernels to estimate the probability density functions of both the experimental and reference populations from two independent samples. Based on these densities, we introduce a quantity called the overlap coefficient or overlap measure. A bootstrap technique is helpful in exploring the distribution and variance empirically. We derive the distribution of this measure and define a hypothesis test that can be applied to the non-inferiority setting under some …
Generalization Of Kullback-Leibler Divergence For Multi-Stage Diseases: Application To Diagnostic Test Accuracy And Optimal Cut-Points Selection Criterion, Chen Mo
College of Graduate Studies: Theses & Dissertations
The Kullback-Leibler divergence (KL), which captures the disparity between two distributions, has been considered as a measure for determining the diagnostic performance of an ordinal diagnostic test. This study applies KL and further generalizes it to comprehensively measure the diagnostic accuracy test for multi-stage (K > 2) diseases, named generalized total Kullback-Leibler divergence (GTKL). Also, GTKL is proposed as an optimal cut-points selection criterion for discriminating subjects among different disease stages. Moreover, the study investigates a variety of applications of GTKL on measuring the rule-in/out potentials in the single-stage and multi-stage levels. Intensive simulation studies are conducted to compare the performance …
Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials, Victor Chukwu
Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials, Victor Chukwu
College of Graduate Studies: Theses & Dissertations
In Clinical Practice, combination drug therapy has become common in treating many disease conditions. The purpose of these combinations is often to ensure optimal efficacy and to reduce adverse effects that may arise from monotherapy. Clinical trials have also been conducted to ensure efficacy and safety of these combinations before they are introduced into the market. However, adverse effects still occur with combination therapies. The objective of this study is to (1) To determine a region of optimum doses of Drug A and Drug B in combination while focusing on efficacy alone (2) To determine a region of optimum doses …
Missing Data In Clinical Trial: A Critical Look At The Proportionality Of Mnar And Mar Assumptions For Multiple Imputation, Theophile B. Dipita
Missing Data In Clinical Trial: A Critical Look At The Proportionality Of Mnar And Mar Assumptions For Multiple Imputation, Theophile B. Dipita
College of Graduate Studies: Theses & Dissertations
Randomized control trial is a gold standard of research studies. Randomization helps reduce bias and infer causality. One constraint of these studies is that it depends on participants to obtain the desired data. Whatever the researcher can do, there is a possibility to end up with incomplete data. The problem is more relevant in clinical trials when missing data can be related to the condition under study. The benefits of randomization is compromised by missing data. Multiple imputation is a valid method of treating missing data under the assumption of MAR. Unfortunately this is an unverified assumptions. Current practice advise …