Web-based software tools for handling missing data in medical questionnaires

Abstract

This thesis will present web-based software tools to handle the problem of missing data in medical questionnaires. Different methods of creating these tools will be analyzed. This study will also lead us to analyse different imputation techniques used to address this problem. It will also provide different ways on how MATLAB can be used with online tools. Medical questionnaires are becoming more popular in examining the emotional and physical effects a chronic disease can have on a patient's lifestyle. Health related quality of life is frequently used in both clinical trials and observational studies. Nursing interventions are aimed at improving the well-being of patients, mainly those suffering from a chronic disease where a cure does not exist. Information about their treatment and feedback about the healthcare in general will be collected in order to optimize the patient's comfort. However, these medical questionnaires, inevitably, will always contain some missing information, which can be detrimental in the analyses of such studies. This study aims to present missing data imputation software accessible through web-based tools, so that analysts and data owners can make use of such software. Different software technologies, languages and techniques will be analyzed, and an application will be implemented using the most appropriate methods.