Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Application of Multiple imputation in Analysis of missing data in a study of Health-related quality of life

Zhu, Chunming (2011) Application of Multiple imputation in Analysis of missing data in a study of Health-related quality of life. Master's Thesis, University of Pittsburgh. (Unpublished)

[img] PDF
Primary Text

Download (1MB)

Abstract

When a new treatment has similar efficacy compared to standard therapy in medical or social studies, the health-related quality of life (HRQL) becomes the main concern of health care professionals and can be the basis for making a decision in patient management. National Surgical Adjuvant Breast and Bowel Protocol (NSABP) C-06 clinical trial compared two therapies: intravenous (IV) fluorouracil (FU) plus Leucovorin (LV) and oral uracil/ftorafur (UFT) plus LV, in treatment of colon cancer. However, there was a high proportion of missing values among the HRQL measurements that only 481 (59.8%) UFT patients and 421 (52.4%) FU patients submitted the forms at all time points. Ignoring the missing data issue often leads to inefficient and sometime biased estimates. The primary objective of this thesis is to evaluate the impact of missing data on the estimated the treatment effect. In this thesis, we analyzed the HRQL data with missing values by multiple imputation. Both model-based and nearest neighborhood hot-deck imputation methods were applied. Confidence intervals for the estimated treatment effect were generated based on the pooled imputation analysis. The results based on multiple imputation indicated that missing data did not introduce major bias in the earlier analyses. However, multiple imputation was worthwhile since the most estimation from the imputation datasets are more efficient than that from incomplete data. These findings have public health importance: they have implications for development of health policies and planning interventions to improve the health related quality of life for those patients with colon cancer.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhu, Chunmingzhuchm@yahoo.com
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairTang, Gongtang@nsabp.pitt.eduGOT1
Committee MemberChu, Tianjiaotchu@mwri.magee.edu
Committee MemberKong, Lanlkong@pitt.eduLKONG
Committee MemberYothers, Gregyothers@nsabp.pitt.eduGAYST3
Date: 29 June 2011
Date Type: Completion
Defense Date: 30 March 2011
Approval Date: 29 June 2011
Submission Date: 5 April 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: missing data; multiple imputation; quality of life
Other ID: http://etd.library.pitt.edu/ETD/available/etd-04052011-152111/, etd-04052011-152111
Date Deposited: 10 Nov 2011 19:34
Last Modified: 15 Nov 2016 13:38
URI: http://d-scholarship.pitt.edu/id/eprint/6791

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item