Category: Research, Design, and Statistics

RICH LIFE: Reducing Hypertension Disparities through Health System vs Multilevel Interventions

The RICH LIFE Study will help to lower blood pressure and heart disease risk among minority, low income, and rural populations, by comparing standard clinical performance feedback and education for providers and staff to a more comprehensive approach that includes workshops for health system leaders, a structured team approach to care, and access to subspecialists […]

Observational Study Overview and Design: An Instrumental Variable Based Approach

Observational Study aims to draw inference about the possible effect of a treatment on subjects from an empirical comparison of treated and controlled groups, which is widely used in all kinds of healthcare and medical research when clinical trials are not applicable in practice. In this presentation, I will focus on the overview of Observational […]

Piecewise Linear Mixed Effects Model in Tracking the Mean Response Trend

Modeling mean response over time and covariance among repeated measures on the same individuals are the main two aspects of longitudinal data analysis. Linear mixed effects models track the mean response as a combination of population characteristics that are assumed to be shared by all individuals and subject-specific effects that are unique to a particular […]

Trauma Research and Performance Improvement

Value Institute Scholars meet regularly to discuss ongoing research projects, various investigative techniques, and current issues from a variety of fields. Our scholars include Value Institute leadership and staff members, as well as clinicians practicing across a broad range of specialties within the Christiana Care Health System. We study pressing issues identified as part of […]

Health Reform and Transformation in Delaware

Misclassification of Sensitive Health Information

Survival Analysis for Multiple Failure Time Data

Multiple failure-time data or multivariate survival data are frequently encountered in medical investigations. These data arise from time-to-occurrence studies when either of two or more events (failures) occur for the same subject, or from identical events occurring to related subjects such as family members or classmates. In these studies, failure times are correlated within cluster […]

Efficient Estimation and Inference in Matrix Regression with Application to Neuroimaging Data and Bioassay Data

Matrix regression is a generalization of conventional multivariate regression. It has potential important applications in contemporary complex structured data, such as data from neuroimaging studies, cross-over design analysis, and multivariate growth curve modeling, among many others. In this talk, I will propose a new enveloping approach to reduce estimation standard errors in multivariate regression and […]

Using Hurdle Models to Analyze Zero-Inflated Count Data

Many outcomes in medical research are counts of some event. For example, heart rate is expressed as a count of beats per minute, or a patient may have more than one infection during an ICU stay, or a patient may be re-hospitalized a number of times following their index hospitalization. When the counts are large, […]

Meta-Analysis: How to Really Lie with Statistics

This presentation examines controversies surrounding the validity and meaningfulness of meta-analysis. Dr. Kolm is Director of Biostatistics at Christiana Care Health System, Research Professor of Medicine at Thomas Jefferson University and Director of the Biostatistical Core of the Bridging Advanced Developments for Exceptional Rehabilitation (BADER) Consortium funded by the Department of Defense. He has over […]