Background: The unprecedented outbreak of COVID-19 in December 2019 necessitated the use of emergency response measures to mitigate the spread of the virus. The state …
The random forest algorithm is a popular non-parametric alternative to more parametric approaches when building risk prediction models. In short, the algorithm averages predictions from …
Time introduces complexity in causal inference for observational studies. This thesis investigates two sources of bias for studies involving time-varying data. One is the missing …
Globally over 34 million people with HIV, with 67% in sub-Saharan Africa alone (UNAIDS) 2009. Data from randomized trials to inform on clinical decisions scarce. …
Provider profiling is used to gauge the level of care that is being offered across providers. The extensive repercussions of provider profiling on the health …
This thesis work is motivated by the specific challenges in analyzing data from clinical trials in behavioral medicine. Specifically, smoking cessation and physical activity trials. …
Abstract of Analysis of temporal trends in opioid prescribing: Assessing the Effectiveness of an opioid prescribing policy using segmented regression, difference in difference versus propensity …
This dissertation presents methods for statistical analysis of social network data. First, we develop a Bayesian hierarchical model that calibrates self and peer-reports in order …
Background: Diagnostic models are useless unless they are valid in the population to which they are applied. The validity of a model often involves measures …
We extend the results presented by Antos et al. [1] for nonparametric estimation methods using complete datasets to nonparametric regression estimators that use right censored …
Prediction and causality are of significant importance in public health and epidemiology. Questions of interest related to predictive modeling include the screening for high risk …
Individual-Level Data (IPD) approach has become increasingly popular as it does not depend on published results. Combining IPD across multiple studies usually adopts a multilevel …
Abstract of Calibrating Transition Probabilities for Tobacco Use in Markov Multi-state Modeling, by Breanna Richards, Degree ScM, Brown University, May 2023 Background and Aims: Tobacco …
Background: Microsimulation models (MSMs), belonging to a class of statistical models that perform simulations at the level of individual units, often persons, have been used …
We present an analysis of hospitalization rates following opioid and non-pharmacologic treatment among Medicare beneficiaries suffering from chronic back pain. Treatment for chronic back pain …
This thesis work is motivated by the specific challenges in analyzing data from behavioral trials. Specifically, SRIDE study designed to increase physical activity. Typically, the …
The gold standard to estimate the causal effect of an exposure on an outcome is a completely randomized design. Randomized designs are attractive for estimating …
Causal mediation analysis is widely applied in the social, economic and biological sciences to assess the causal mechanism between three variables: a treatment, an intermediate …
Two key populations affected by HIV are patients co-infected with Tuberculosis (TB) and children. It is not always advisable to initiate combination antiretroviral therapy (cART) …