Current Research

Product Partitioned Dirichlet Process Prior Models for Identifying Substantive Clusters and Fitted Subclusters

Product Partitioned Dirichlet Process Prior Models for Identifying Substantive Clusters and Fitted Subclusters in Mouse Model Data and Terrorism Data. With Andrew Womack, Indiana University Department of Statistics. This work introduces a new model-based clustering design which incorporates two sources of heterogeneity for the modeling of social science data. The first source of heterogeneity is in the residuals from the mean structure and is modeled with Dirichlet Process random effects.  The second source of heterogeneity is unobserved grouping in the data, which is modeled using the product partition framework.  Incorporating both sources of inhomogeneity allows the model to capture both structural differences in response to the covariates as well as departures from normality in the error structure.  The model is applied to the analysis of terrorist groups, which shows how this tool reveals important features in a dataset that are otherwise undetectable.

A Bayesian Kriging Approach to Measuring State Ideology with Spatial Realignment

Anemia is common during critical illness and is associated with increased mortality. Paradoxically, anemia correction in this setting commonly confers additional risk, rather than benefit. Current transfusion decision making appears deceptively sim- ple: administer red blood cells (RBCs) to correct anemia below set hemoglobin [Hb] thresholds; however, this approach does not consider additional factors that are both (1) fundamental to efficacy and (2) exhibit striking variance (e.g. illness severity and trajec- tory, anemia tolerance, vulnerability to harms). Contextualizing anemia significance by inclusion of these factors in a personalized decision making system may improve prediction of transfusion benefit. Here, we propose a novel approach, grounded upon outcome-linked, physiologically integrated biologic efficacy targets and tactics for transfusion (BETTr). The BETTr conceptual model is developed into a “proof of concept” computer simulation. The BETTr conceptual model replicates the dynamic patterns seen based on current clin- ical guidelines, and depicts the alternative guideline for transfusion decisions using the probability of recovery estimated from monitoring fitness (iDO2), compensatory reserve (CRI) in addition to anemia (AI). The BETTr conceptual model is then used to generate a synthetic data set for demonstrating the feasibility of the approach to estimating the probability of recovery.

Spike and Slab Prior Distributions for Simultaneous Bayesian Hypothesis Testing, Model Selection, and Prediction, of Nonlinear O

Spike and Slab Prior Distributions for Simultaneous Bayesian Hypothesis Testing, Model Selection, and Prediction, of Nonlinear Outcomes. 

With Xun Pang, Tsinghua University.  A small body of literature has used the spike and slab prior specification for model selection with strictly continuous outcomes. In this setup a two-component mixture distribution is stipulated for coefficients of interest with one part centered at zero with very high precision (the spike) and the other as a distribution diffusely centered at the research hypothesis (the slab). With selective shrinkage, this setup incorporates the zero coefficient contingency directly into the modeling process to produce posterior probabilities for hypothesized outcomes. We extend the model to qualitative responses by designing a hierarchy of forms over both the parameter and model spaces to achieve variable selection, model averaging, and individual coefficient hypothesis testing.  The performance of the models and methods are assessed with empirical applications in political science.

The Variable Effect of War on Longterm Childhood Mental Health Outcomes. 

The Variable Effect of War on Longterm Childhood Mental Health Outcomes. 

With Enbal Shacham, Saint Louis University Behavioral Science and Health Education..  We propose to add to the understanding of the adverse affects of war on children by simultaneously leveraging three areas of expertise and unique access to affected subjects.  The two principle investigators provide combined expertise in psychologicigal epidemiology, statistics, and political science.  It is important to understand this problem from all of these perspectives since their effects are intermingled and interrelated.  Currently there is no study offering this combination of perspectives.  At the origin this is a political problem since malevelent, disfunctional, or aggressive governments and non-state entities foment violence for bureaucratic, economic, and personal ambitions.  It should also be viewed as an epidemiological subject since it distributes adverse health outcomes in a contageous, geographic, and enduring manner.  While the physical casualties are often substantial, we focus here on the long-term psychological damage that may follow these children for much of their lives.  We intend to execute a truly interdisciplinary study where the political science, the epidemiology, the psychology, and the statistical analysis are all done to the highest standards of each discipline. 

Queueing Theory Models for Political Science Data

Queueing Theory Models for Political Science Data  

Queueing theory is widely used in many literatures to describe assembly-line type processes, and services in which the completion time is indeterminant. However, there are almost no applications of queueing theory in political science. This is curious because political actors queue up for desired benefits under a number of circumstances. This project looks at the theoretical and practical basis for applying of queueing theory to the analysis of institutional politics.  Empirical applications include the process of bills through legislatures, the scheduling and hearing of court cases, and initiatives within international institutions.  

Assessing Changes in Rapid Response Protocols for Pediatric Intensive Care

Assessing Changes in Rapid Response Protocols for Pediatric Intensive Care

With Mary Hartman, Nikoleta Kolovos, and Allan Doctor, Washington University School of Medicine.  We are fundamentally concerned with resource use at the time of PICU admission in the period before and after changes in interventions.  To test the efficacy of the rapid response team (RRT) approach we collected data from the Childrens' Hospital Pediatric Intensive Care Unit (PICU) for the period 2010 to 2013.  This produced 2152 patient records: 1097 pre-program implementation cases and $1055$ post-program implementation cases, which is nearly balanced.  The variable PrePostRRT is coded 0 for pre-program and 1 for post-program.  This is the key explanatory variable in our statistical models, and its multidimensional relationship with the other variables is the source of our conclusions below. Our modeling approach includes statistical assessment of divergent measures with generalized Bayesian measurement models.       

Physiologically Integrated Biologic Efficacy Targets and Tactics for Transfusion (BETTr)

Anemia is common during critical illness and is associated with increased mortality. Paradoxically, anemia correction in this setting commonly confers additional risk, rather than benefit. Current transfusion decision making appears deceptively sim- ple: administer red blood cells (RBCs) to correct anemia below set hemoglobin [Hb] thresholds; however, this approach does not consider additional factors that are both (1) fundamental to efficacy and (2) exhibit striking variance (e.g. illness severity and trajec- tory, anemia tolerance, vulnerability to harms). Contextualizing anemia significance by inclusion of these factors in a personalized decision making system may improve prediction of transfusion benefit. Here, we propose a novel approach, grounded upon outcome-linked, physiologically integrated biologic efficacy targets and tactics for transfusion (BETTr). The BETTr conceptual model is developed into a “proof of concept” computer simulation. The BETTr conceptual model replicates the dynamic patterns seen based on current clin- ical guidelines, and depicts the alternative guideline for transfusion decisions using the probability of recovery estimated from monitoring fitness (iDO2), compensatory reserve (CRI) in addition to anemia (AI). The BETTr conceptual model is then used to generate a synthetic data set for demonstrating the feasibility of the approach to estimating the probability of recovery.

Selected Current Research: Jeff Gill, Updated 5/31/18.                   

JEFF GILL

Distinguished Professor, Department of Government

Professor, Department of Mathmatics & Statistics, Member, Center for Behavioral Neuroscience
American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016
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