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Roumani, Yazan (2006) ACCOUNTING FOR MONOTONE ATTRITION IN A POSTPARTUM DEPRESSION CLINICAL TRIAL. Master's Thesis, University of Pittsburgh. (Unpublished)

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Longitudinal studies in public health, medicine and the social sciences are often complicated by monotone attrition, where a participant drops out before the end of the study and all his/her subsequent measurements are missing. To obtain accurate non-biased results, it is of public health importance to utilize appropriate missing data analytic methods to address the issue of monotone attrition.The defining feature of longitudinal studies is that several measurements are taken for each participant over time. The commonly used methods to analyze incomplete longitudinal data, complete case analysis and last observation carried forward, are not recommended because they produce biased estimators. Simple imputation and multiple imputation procedures provide alternative approaches for addressing monotone attrition. However, simple imputation is difficult in a multivariate setting and produces biased estimators. Multiple imputation addresses those shortcomings and allows a straightforward assessment of the sensitivity of inferences to various models for non-response. This thesis reviews the literature on missing data mechanisms and missing data analysis methods for monotone attrition. Data from a postpartum depression clinical trial comparing the effects of two drugs (Nortriptyline and Sertraline) on remission status at 8 weeks were re-analyzed using these methods. The original analysis, which only used available data, was replicated first. Then patterns and predictors of attrition were identified. Last observation carried forward, mean imputation and multiple imputation were used to account for both monotone attrition and a small number of intermittent missing measurements. In multiple imputation, every missing measurement was imputed 6 times by predictive matching. Each of the 6 completed data sets was analyzed separately and the results of all the analyses were combined to get the overall estimate and standard errors. In each analysis, continuous remission levels were imputed but the probability of remission was analyzed. The original conclusion of no significant difference in probability of remission at week 8 between the two drug groups was sustained even after carrying the missing measurements forward, mean and multiple imputations. Most drop outs occurred during the first three weeks and participants taking Sertraline who live alone were more likely to drop out.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairStone, Roslyn Aroslyn@pitt.eduROSLYN
Committee MemberHanusa, Barbara Hbhhmq@pitt.eduBHHMQ
Committee MemberMazumdar, Satimaz1@pitt.eduMAZ1
Date: 25 September 2006
Date Type: Completion
Defense Date: 24 July 2006
Approval Date: 25 September 2006
Submission Date: 3 August 2006
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: monotone attrition; clinical trial; longitudinal data; multiple imputation
Other ID:, etd-08032006-152442
Date Deposited: 10 Nov 2011 19:56
Last Modified: 15 Nov 2016 13:47


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