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.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-4649 |
| Date | 01 January 2014 |
| Creators | He, Jun |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © The Author |
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