Jun HeFollow

Defense Date


Document Type


Degree Name

Master of Science



First Advisor

Dr. Donna McClish

Second Advisor

Professor Russell Boyle

Third Advisor

Dr. John Quillin


The main purpose of this research was to evaluate use of Last Observation Carried Forward (LOCF) as an imputation method when persistent binary outcomes are missing in a Randomized Controlled Trial. A simulation study was performed to see the effect of dropout rate and type of dropout (random or associated with treatment arm) on Type I error and power. Properties of estimated event rates, treatment effect, and bias were also assessed. LOCF was also compared to two versions of complete case analysis - Complete1 (excluding all observations with missing data), and Complete2 (only carrying forward observations if the event is observed to occur). LOCF was not recommended because of the bias. Type I error was increased, and power was decreased. The other two analyses also had poor properties. LOCF analysis was applied to a mammogram dataset, with results similar to the simulation study.


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Date of Submission


Available for download on Tuesday, December 10, 2019