Digital Commons Network^™

Epidemiologic Evaluation Of Nhanes For Environmental Factors And Periodontal Disease, P. Emecen-Huja, H. -F. Li, J. L. Ebersole, J. Lambert, Heather M. Bush

Biostatistics Faculty Publications

Periodontitis is a chronic inflammation that destroys periodontal tissues caused by the accumulation of bacterial biofilms that can be affected by environmental factors. This report describes an association study to evaluate the relationship of environmental factors to the expression of periodontitis using the National Health and Nutrition Examination Study (NHANES) from 1999–2004. A wide range of environmental variables (156) were assessed in patients categorized for periodontitis (n = 8884). Multiple statistical approaches were used to explore this dataset and identify environmental variable patterns that enhanced or lowered the prevalence of periodontitis. Our findings indicate an array of environmental variables were …

Measurement Of Bystander Actions In Violence Intervention Evaluation: Opportunities And Challenges, Heather M. Bush, Samuel C. Bell, Ann L. Coker

Biostatistics Faculty Publications

Purpose of Review

This review discusses design and methodological challenges specific to measuring bystander actions in the evaluation of bystander-based violence prevention programming. “Bystanders” are defined as people who are present immediately before, during and/or after a violent event, but are not a perpetrator nor the intended victim. Bystander-based violence prevention programs seek to prevent or mitigate violent events by empowering bystanders to intervene on acts of violence and social norms that promulgate violence.

Recent Findings

Effective bystander-based violence prevention programs demonstrate increased bystander intentions, actions, and attitudes [Bringing in the Bystander: Banyard et al. J Community Psychol. 2007;35:463-481; iSCREAM: …

Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang

Biostatistics Faculty Publications

To analyze gene expression data with sophisticated grouping structures and to extract hidden patterns from such data, feature selection is of critical importance. It is well known that genes do not function in isolation but rather work together within various metabolic, regulatory, and signaling pathways. If the biological knowledge contained within these pathways is taken into account, the resulting method is a pathway-based algorithm. Studies have demonstrated that a pathway-based method usually outperforms its gene-based counterpart in which no biological knowledge is considered. In this article, a pathway-based feature selection is firstly divided into three major categories, namely, pathway-level selection, …

Feature Selection For Longitudinal Data By Using Sign Averages To Summarize Gene Expression Values Over Time, Suyan Tian, Chi Wang

Biostatistics Faculty Publications

With the rapid evolution of high-throughput technologies, time series/longitudinal high-throughput experiments have become possible and affordable. However, the development of statistical methods dealing with gene expression profiles across time points has not kept up with the explosion of such data. The feature selection process is of critical importance for longitudinal microarray data. In this study, we proposed aggregating a gene’s expression values across time into a single value using the sign average method, thereby degrading a longitudinal feature selection process into a classic one. Regularized logistic regression models with pseudogenes (i.e., the sign average of genes across time as predictors) …