Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/5153
Title: Modeling Medical Data Using MM-Estimation Applied to Body Mass Index Data.
Authors: Nor Azlida Aleng
Keywords: Nyi Nyi Naing
Zurkurnai Yusof
Norizan Mohamed
Robust regression
MM-estimation
Outliers
Issue Date: 2015
Publisher: Applied Mathematical Sciences
Abstract: In medical statistics research, there are many methodologies used to investigate and to model the relationship between two or more variables. A model is often not useful when its fails to fit the data and the outliers may exist. Outliers play important role in regression. An outliers (observations) that is quite different from most the other values or observations in a data set. Robust regression is the most popular method that has been used to detect outliers and to provide resistant results in the presence of outliers in the data set. The purpose of this study is to show that, robust MM-estimation is an alternative approach in dealing with outliers presence in the medical data. This approach is extremely useful in identifying outliers and assessing the adequacy of a fitted model
URI: http://hdl.handle.net/123456789/5153
ISSN: 1662-7482
Appears in Collections:Journal Articles

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