Analyzing Data from Older Study Samples: What Should the Toolkit of a Gerontologic Biostatistician Include?

• Activity Number: 425
• Type: Roundtables
• Date/Time: Wednesday, August 6, 2014 : 7:00 AM to 8:15 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Peter Van Ness*+
• Companies: Yale School of Medicine
• Keywords: Gerontology ; Bayesian ; Nursing Home ; Missing Data ; Nonparametric ; Multivariate Data

Abstract

Contemporary statisticians can draw statistical inferences in many circumstances using different inferential frameworks. Frequentist, Bayesian, nonparametric (e.g., exact), and structural equation modeling (SEM) are especially common alternative frameworks. An accomplished statistician will know the distinctive advantages and disadvantages of these various frameworks for particular types of statistical inference. This roundtable discussion will focus on which of these basic methodological frameworks is most appropriate for specific statistical challenges that arise in clinical biomedical research conducted with older study participants. Such challenges include missing data occurring because of high morbidity and mortality among older persons, data dependencies occurring because of distinctive living situations of older persons (e.g., in nursing homes), multivariate data occurring because of multiple morbidities and multicomponent interventions, and data that are both quantitative and qualitative occurring because quality of life and medical decisionmaking issues are prominent at the end of life.