Physical Sciences and Mathematics Commons^™

Tree-Based Methods And A Mixed Ridge Estimator For Analyzing Longitudinal Data With Correlated Predictors, Melissa Nicole Eliot

Open Access Dissertations

Due to recent advances in technology that facilitate acquisition of multi-parameter defined phenotypes, new opportunities have arisen for predicting patient outcomes based on individual specific cell subset changes. The data resulting from these trials can be a challenge to analyze, as predictors may be highly correlated with each other or related to outcome within levels of other predictor variables. As a result, applying traditional methods like simple linear models and univariate approaches such as odds ratios may be insufficient. In this dissertation, we describe potential solutions including tree-based methods, ridge regression, mixed modeling, and a new estimator called a mixed …