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 …
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 …
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 …
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 …
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 …
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 …
Abstract of Comparative Effectiveness of EFA and MFA for Estimation of Alzheimer’s Disease Cognitive Biomarkers , by Joanna Walsh, Sc.M., Brown University, May 2022. Exploratory …
Background. Rituximab-based immunochemotherapy for Waldenström macroglobulinemia / lymphoplasmacytic lymphoma (WM/LPL) showed high response rates in single-arm trials, but comparative data are lacking. We compared overall …
Background: The 16S rRNA amplicon sequencing is a widely-used method for characterizing microbial communities. Recently, a bioinformatics pipeline (Kraken) has been proposed to infer microbiome …
Background: Randomized clinical trials (RCTs) are considered the gold standard approach for assessing the comparative effectiveness of medical interventions. Given the importance of RCTs for …
In data analysis, simultaneously performing multiple hypothesis tests will increase error rates. The multiple testing problem is common across different field of studies including microarray …
Single cell RNA sequencing (scRNA-seq) is a recently developed technology that enables the quantification of RNA transcripts at individual cell level, providing cellular level resolution …
