The Role of Missing Data Imputation in Clinical Studies
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University of Cincinnati / OhioLINK
2018
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Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535705430538222 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin15357054305382222021-08-03T07:08:29Z The Role of Missing Data Imputation in Clinical Studies Peng, Zhimin Biostatistics missing data imputation Clinical Studies Missing data is a common problem in clinical study. Removing missing data with complete case analysis (CCA) could lower power and bias the statistical conclusion. A variety of approaches have been used to deal with missing data. Several basic imputation methods would be introduced in this study. With the datasets derived from Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study, group mean imputation (Gmean), total mean imputation (Tmean), expectation-maximization (EM) Algorithm, Markov chain Monte Carlo (MCMC) and fully conditional specification (FCS) imputation methods will be compared. Mean absolute error (MAE), root mean squared error (RMSE), mean of parameter bias, standard error of parameter bias will be used as evaluation criteria. Our results suggest that FCS is the rigorous statistical procedure for rare event data with high missing rate and binary outcome, which deserves more application in practice. 2018 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535705430538222 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535705430538222 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
language |
English |
sources |
NDLTD |
topic |
Biostatistics missing data imputation Clinical Studies |
spellingShingle |
Biostatistics missing data imputation Clinical Studies Peng, Zhimin The Role of Missing Data Imputation in Clinical Studies |
author |
Peng, Zhimin |
author_facet |
Peng, Zhimin |
author_sort |
Peng, Zhimin |
title |
The Role of Missing Data Imputation in Clinical Studies |
title_short |
The Role of Missing Data Imputation in Clinical Studies |
title_full |
The Role of Missing Data Imputation in Clinical Studies |
title_fullStr |
The Role of Missing Data Imputation in Clinical Studies |
title_full_unstemmed |
The Role of Missing Data Imputation in Clinical Studies |
title_sort |
role of missing data imputation in clinical studies |
publisher |
University of Cincinnati / OhioLINK |
publishDate |
2018 |
url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535705430538222 |
work_keys_str_mv |
AT pengzhimin theroleofmissingdataimputationinclinicalstudies AT pengzhimin roleofmissingdataimputationinclinicalstudies |
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1719454635674042368 |