Abstract:
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The most widely used general health outcomes measure is the SF-36 Health Status questionnaire. The SF-36 is a thirty-six item general health survey that evaluates eight dimensions of health. This questionnaire is therapeutic non-specific. Often times, analysis is done to determine if a subject's quality of life is better on one drug than another. This can be beneficial when marketing a drug. Thus, the SF-36 form is often used in clinical trials. One problem that is often encountered during a clinical trial is missing data. The current method for dealing with missing data might not be the best. In this paper, we develop a new method to estimate missing responses in quality of life data. We present simulation studies to validate our proposed method. This method is applied to data from a clinical trial conducted by GlaxoSmithKline Pharmaceutical company. The trial is an open-label, multinational, parallel group study to evaluate the impact of oral Naratriptan 2.5mg on migraines. The current method of evaluating SF-36 data converts the data into eight score functions and treats the score functions as continuous data. When applying our method, we will treat the data as categorical.
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