Dissertation

Detecting Changes in Cancer-Related Cognitive Functioning Using Mixed-Effects Modeling and Study Design Simulations

Clapp, Jonathan D

2024

Overview

The purpose of this dissertation is to utilize and compare two existing approaches for modeling nonlinear change in cognitive functioning in cancer patients over time and to assess alternative study designs to better capture chemotherapy-related cognitive impairment using simulation data. Using data from the Thinking and Living with Cancer study, trend analysis with orthogonal polynomials (OP) and piecewise (PW) regressions approaches used to analyze cognitive functioning trajectories. Simulated datasets tested the impact of study design parameters including measurement test-retest reliability (.6 or .8), sample size (100, 200, or 300), and the number of data collection time points (4 or 5) on observed power and effect size under different conditions. In the TLC data, the PW approach accounted for a higher amount of the group by time interaction effect compared to the OP approach (71.3% vs. 56.1%, respectively). For the values used in present simulations, sample sizes and test-retest reliabilities were the predominant factors affecting statistical power for detecting significant group by time interactions. Focusing on the effect sizes of the interaction terms, it was clear that reliability was the most important factor regardless of the approach being used. Cancer patients are reporting smaller cognitive deficits compared to patients with other illnesses, which dictates samples will need to be quite large in order to have adequate power. However, higher reliability gets more power and adding time points can improve power, but instruments with lower reliability tend to make power worse.

• Publisher: ProQuest Dissertations & Theses
• Subject: Bioinformatics / Biostatistics / Cognitive psychology / Epidemiology / Oncology / Public health
• ISBN: 9798346813033