Applying meta-analysis methods in multiple sclerosis clinical trials

Meta-analysis, or the statistical method used to combine results from two or more separate studies, provides the ability to answer important clinical questions. Clinical trial data are generated using rigorous methods and associated with a high level of evidence for medical decision-making. Increasing accessibility to clinical trial data creates unique opportunities to investigate important clinical questions with high quality data that may have been beyond the original intention of the individual study.

Is obesity less harmful in older adults? The challenge of studying a lifelong exposure under dynamic confounding, selection, and misclassification

The effect of obesity on morbidity and mortality in childhood and middle age has been studied extensively, but there is still an ongoing debate about whether obesity poses a health risk to older adults. There is some evidence suggesting that obesity is not associated with mortality in older adults, and in fact, may confer some degree of protection. Questions about the effect of obesity in old age are particularly salient with respect to older women because the hormone changes that occur during menopause are associated with weight gain and changes in the distribution of adipose tissue.

Random Measures, ANOVA models, and Uncertainty Quantification of Randomized Controlled Trials

In this talk, Bastian will discuss a novel approach to global sensitivity analysis grounded in the variance-covariance structure of random variables derived from random measures. The proposed methodology facilitates the application of information-theoretic rules for uncertainty quantification, offering several advantages. Specifically, the approach provides valuable insights into the decomposition of variance within discrete subspaces, similar to the standard ANOVA analysis.

Faculty Speed Talks

Faculty Presentations

  • Rebecca Andridge, Biostatistics, Ohio State College of Public Health
    "Sensitivity Analysis for Non-ignorable Sample Selection in Nonprobability Samples"
  • Max Russo, Statistics, CAS
    "Exploring Tree-Based Scan Statistics for Mining of Adverse Drug Events"
  • Xiaoxuan Cai, Statistics, CAS
    "Causal Inference in Mobile Device Data"
  • Boseung Choi, Division of Big Data Science, Korea University
    "Statistical Method of Identification for the Relationship between Prevalence and Wastewater Concentration of COVID-19"
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