Term of Award
Doctor of Public Health in Biostatistics (Dr.P.H.)
Document Type and Release Option
Dissertation (restricted to Georgia Southern)
Copyright Statement / License for Reuse
Digital Commons@Georgia Southern License
Department of Biostatistics (COPH)
Committee Member 1
Committee Member 2
In this dissertation, we simulated (1000 replications) diastolic blood pressure (DBP) data to model a Phase III clinical trial in newly diagnosed hypertensive patients that had 8 consecutive days of baseline run-in data followed by six months of double-blind, randomized treatment with either a drug or placebo. We considered six different patterns (3 linear, 3 non-linear) of baseline run-in DBP data, prior to randomizing patients to treatment with a drug or placebo in balanced fashion (50 per group). We defined 11 functions of the baseline run-in data for use as covariates. Comparative statistical analyses were performed using both repeated measures linear ANCOVA models and longitudinal data analysis models-with or without treatment-by-time interaction and with or without the covariates and assuming the DBP data truncated to the interval (80; 120] mmHg followed either AR (1) or CS covariance structure with correlation coefficients of 0.1, 0.5 and 0.9. Our primary objective was to determine the best function of the baseline run-in data to use as a covariate in the comparative statistical analysis of the monthly treatment period data. As a secondary objective, we assessed whether 8 days of baseline run-in data were needed or whether fewer numbers of days would suffice.
Hao, Yi, "Choosing the Function of Baseline Run-in Data for use as a Covariate in the Analysis of Treatment Data from Phase III Clinical Trials in Hypertension" (2016). Electronic Theses and Dissertations. 1482.
Research Data and Supplementary Material