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
Available for download on Saturday, September 11, 2021