Abstract

In this thesis, the basics of smoothing spline analysis of variance are first introduced. Regular physical activity has been shown to reduce the risk of chronic diseases in older adults, such as heart disease, stroke, diabetes, and certain forms of cancer. Accurate measurement of physical activity levels in older adults is crucial to identify those who may require interventions to increase their activity levels and prevent functional decline. In our study, we collected data on the physical activity of older individuals by utilizing accelerometer accelerometers. To estimate the underlying patterns related to each covariate, we applies smoothing spline analysis of variance (SSANOVA) methods to two types of measurements from the accelerometer device. We investigates the underlying patterns of different participant groups and compared the patterns among groups. The paper reveals clear patterns of activity levels throughout the day and across days, with differences among groups observed. Additionally, the study compares the mean curve method and the SSANOVA model, and shows that the SSANOVA model is a more suitable method for analyzing physical activity data. The study provides valuable insights into daily physical activity patterns in older people and highlights the usefulness of the SSANOVA model for such data analysis.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu.

Graduation Date

2023

Semester

Spring

Advisor

Xie, Rui

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Statistics & Data Science

Degree Program

Statistics and Data Science; Data Science Track

Identifier

CFE0009851; DP0028157

URL

https://purls.library.ucf.edu/go/DP0028157

Language

English

Release Date

November 2024

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Campus-only Access)

Download

Restricted to the UCF community until November 2024; it will then be open access.

Share

COinS