Physical Sciences and Mathematics Commons^™

Evaluating Trajectories Of Episodic Memory In Normal Cognition And Mild Cognitive Impairment: Results From Adni, Xiuhua Ding, Richard J. Charnigo, Frederick A. Schmitt, Richard J. Kryscio, Erin L. Abner, Alzheimer’S Disease Neuroimaging Initiative

Statistics Faculty Publications

BACKGROUND: Memory assessment is a key factor for the diagnosis of cognitive impairment. However, memory performance over time may be quite heterogeneous within diagnostic groups.

METHOD: To identify latent trajectories in memory performance and their associated risk factors, we analyzed data from Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who were classified either as cognitively normal or as Mild Cognitive Impairment (MCI) at baseline and were administered the Rey Auditory Verbal Learning test (RAVLT) for up to 9 years. Group-based trajectory modeling on the 30-minute RAVLT delayed recall score was applied separately to the two baseline diagnostic groups.

RESULTS: There were …

Comparing Performance Of Non-Tree-Based And Tree-Based Association Mapping Methods, Katherine L. Thompson, David W. Fardo

Statistics Faculty Publications

A central goal in the biomedical and biological sciences is to link variation in quantitative traits to locations along the genome (single nucleotide polymorphisms). Sequencing technology has rapidly advanced in recent decades, along with the statistical methodology to analyze genetic data. Two classes of association mapping methods exist: those that account for the evolutionary relatedness among individuals, and those that ignore the evolutionary relationships among individuals. While the former methods more fully use implicit information in the data, the latter methods are more flexible in the types of data they can handle. This study presents a comparison of the 2 …

Mixtures Of Self-Modelling Regressions, Rhonda D. Szczesniak, Kert Viele, Robin L. Cooper

Statistics Faculty Publications

A shape invariant model for functions f₁,...,f_n specifies that each individual function f_i can be related to a common shape function g through the relation f_i(x) = a_ig(c_ix + d_i) + b_i. We consider a flexible mixture model that allows multiple shape functions g₁,...,g_K, where each f_i is a shape invariant transformation of one of those g_K. We derive an MCMC algorithm for fitting the model using Bayesian Adaptive Regression Splines (BARS), propose …