Abstract
In this presentation, we use a multiple regression analysis technique to build a regression model to predict body mass index (BMI) for a person given some predictors like age, height, weight, waist, gender, etc. Data from the U.S department of health and human services, national center for health statistics, third national health and nutrition examination survey will be used to build the regression model. We will use the method of least squares to fit the data and get estimates of the parameters. Predictors will be tested for significance, model assumptions will be checked, and model diagnostics will be used to check the appropriateness of the suggested model. The proposed model will be tested for multicollinearity and autocorrelation. The proposed model will be tested and results will be compared with existing techniques, e.g. charts.
Faculty Sponsors
Dr. Ahmed Albatineh
Project Type
Event
Location
Alvin Sherman Library
Start Date
4-3-2009 12:00 AM
End Date
4-3-2009 12:00 AM
Modeling Health Care Data Using Regression Analysis
Alvin Sherman Library
In this presentation, we use a multiple regression analysis technique to build a regression model to predict body mass index (BMI) for a person given some predictors like age, height, weight, waist, gender, etc. Data from the U.S department of health and human services, national center for health statistics, third national health and nutrition examination survey will be used to build the regression model. We will use the method of least squares to fit the data and get estimates of the parameters. Predictors will be tested for significance, model assumptions will be checked, and model diagnostics will be used to check the appropriateness of the suggested model. The proposed model will be tested for multicollinearity and autocorrelation. The proposed model will be tested and results will be compared with existing techniques, e.g. charts.
