4 citations · 10 across the 8 of their papers we have counts for
9 papers
Adjustment for Biased Sampling Using NHANES Derived Propensity Weights
Olivia M. Bernstein, Brian G. Vegetabile, Christian R. Salazar +2
The Consent-to-Contact (C2C) registry at the University of California, Irvine collects data from community participants to aid in the recruitment to clinical research studies. Self…
A Measurement of In-Betweenness and Inference Based on Shape Theories
Dustin Pluta, Xiangmin Xu, Daniel L. Gillen +1
We propose a statistical framework to investigate whether a given subpopulation lies between two other subpopulations in a multivariate feature space. This methodology is motivated…
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning
Lars Hertel, Pierre Baldi, Daniel L. Gillen
Reinforcement learning algorithms can show strong variation in performance between training runs with different random seeds. In this paper we explore how this affects hyperparamet…
A Flexible Joint Longitudinal-Survival Modeling Framework for Incorporating Multiple Longitudinal Biomarkers
Sepehr Akhavan-Masouleh, Alexander Vandenberg-Rodes, Babak Shahbaba +1
We are interested in survival analysis of hemodialysis patients for whom several biomarkers are recorded over time. Motivated by this challenging problem, we propose a general fram…
A Bayesian Framework for Non-Collapsible Models
Sepehr Akhavan Masouleh, Babak Shahbaba, Daniel L. Gillen
In this paper, we discuss the non-collapsibility concept and propose a new approach based on Dirichlet process mixtures to estimate the conditional effect of covariates in non-coll…
A Flexible Joint Longitudinal-Survival Model for Analysis of End-Stage Renal Disease Data
Sepehr Akhavan Masouleh, Tracy Holsclaw, Babak Shahbaba +1
We propose a flexible joint longitudinal-survival framework to examine the association between longitudinally collected biomarkers and a time-to-event endpoint. More specifically,…
Assessing Health Care Interventions via an Interrupted Time Series Model: Study Power and Design Considerations
Maricela Cruz, Daniel L. Gillen, Miriam Bender +1
The delivery and assessment of quality health care is complex with many interacting and interdependent components. In terms of research design and statistical analysis, this comple…
Fisher information matrix of binary time series
Xu Gao, Hernando Ombao, Daniel Gillen
A common approach to analyzing categorical correlated time series data is to fit a generalized linear model (GLM) with past data as covariate inputs. There remain challenges to con…
Estimating prediction error for complex samples
Andrew Holbrook, Thomas Lumley, Daniel Gillen
With a growing interest in using non-representative samples to train prediction models for numerous outcomes it is necessary to account for the sampling design that gives rise to t…