Matching Items (3)
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Description
This study concerns optimal designs for experiments where responses consist of both binary and continuous variables. Many experiments in engineering, medical studies, and other fields have such mixed responses. Although in recent decades several statistical methods have been developed for jointly modeling both types of response variables, an effective way

This study concerns optimal designs for experiments where responses consist of both binary and continuous variables. Many experiments in engineering, medical studies, and other fields have such mixed responses. Although in recent decades several statistical methods have been developed for jointly modeling both types of response variables, an effective way to design such experiments remains unclear. To address this void, some useful results are developed to guide the selection of optimal experimental designs in such studies. The results are mainly built upon a powerful tool called the complete class approach and a nonlinear optimization algorithm. The complete class approach was originally developed for a univariate response, but it is extended to the case of bivariate responses of mixed variable types. Consequently, the number of candidate designs are significantly reduced. An optimization algorithm is then applied to efficiently search the small class of candidate designs for the D- and A-optimal designs. Furthermore, the optimality of the obtained designs is verified by the general equivalence theorem. In the first part of the study, the focus is on a simple, first-order model. The study is expanded to a model with a quadratic polynomial predictor. The obtained designs can help to render a precise statistical inference in practice or serve as a benchmark for evaluating the quality of other designs.
ContributorsKim, Soohyun (Author) / Kao, Ming-Hung (Thesis advisor) / Dueck, Amylou (Committee member) / Pan, Rong (Committee member) / Reiser, Mark R. (Committee member) / Stufken, John (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Myeloproliferative neoplasm (MPN) patients suffer from fatigue and a reduced overall quality of life, both of which are not resolved with current pharmacologic therapy. The purpose of this study was to examine the effects of a 12-week online-streamed yoga intervention on fatigue and QoL in MPN patients as compared to

Myeloproliferative neoplasm (MPN) patients suffer from fatigue and a reduced overall quality of life, both of which are not resolved with current pharmacologic therapy. The purpose of this study was to examine the effects of a 12-week online-streamed yoga intervention on fatigue and QoL in MPN patients as compared to a wait-list control group as well as to determine the feasibility of remotely collecting blood and saliva samples in a national sample. MPN patients were asked to complete 60 min/week of online yoga for 12 weeks. MPN fatigue and QoL were assessed online with single-item questions taken from the MPN SAF (fatigue and QoL) and NIH PROMIS (QoL) at baseline, week 7, and week 12. The practicality of the blood and saliva measures were defined as >70% completion rate at both baseline and week 12. Fidelity of the intervention (i.e., weekly yoga participation) was assessed via both self-report (i.e., daily log) and objective measurement (i.e., Clicky). Of the 62 MPN patients that enrolled in the study, 48 completed the intervention with 27 participating in the yoga group and 21 participating in the wait-list control group. Weekly yoga participation averaged ~41 min/week as measured objectively, whereas self-report yoga participation averaged ~56 min/week. The blood draw was determined to be practical with a 92.6% completion rate at baseline and a 70.4% completion rate at week 12. There were no significant differences from baseline to week 12 in MPN SAF fatigue (ES=0.18; p=0.724) or MPN SAF QoL (ES=-0.53; p=0.19), however, NIH PROMIS QoL was significantly improved from baseline to week 12 (ES=0.7; p=0.031) when compared to the control group. This study builds upon the findings from a prior feasibility study in demonstrating the feasibility of online yoga as well as its preliminary effects of improving total symptom burden, fatigue, pain, depression, anxiety, and sleep disturbance in MPN patients. Given the effects of yoga demonstrated both in the feasibility study and the current pilot study, a future randomized controlled trial with a larger sample size is warranted in order to further investigate the effectiveness of online yoga for MPN patient symptom burden and QoL.
ContributorsEckert, Ryan (Author) / Huberty, Jennifer (Thesis advisor) / Mesa, Ruben (Committee member) / Gowin, Krisstina (Committee member) / Dueck, Amylou (Committee member) / Kosiorek, Heidi (Committee member) / Larkey, Linda (Committee member) / Arizona State University (Publisher)
Created2017
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Description

Objective: To determine if patients’ insurance status or the income level of their zip code of residence affect their quality of life or overall survival after enrollment in clinical trials for cancer treatment. Methods: Data were collected from cancer treatment trials conducted through the North Central Cancer Treatment Group and

Objective: To determine if patients’ insurance status or the income level of their zip code of residence affect their quality of life or overall survival after enrollment in clinical trials for cancer treatment. Methods: Data were collected from cancer treatment trials conducted through the North Central Cancer Treatment Group and the Alliance for Clinical Trials in Oncology. 700 subjects with baseline quality of life scores were analyzed to explore potential differences in quality of life indicators by insurance group. 624 patients with valid US zip codes were also analyzed based on the median household income of their zip code to determine any associations with quality of life. Overall survival was also analyzed by insurance group and by income quartile. Results: 700 subjects (mean age 59 years, 53% male) were included. 49% had private insurance only, 30% had public insurance only, 8.9% had both private and public insurance, 1.4% had no insurance, and 10% had other insurance. 13% of patients came from zip codes in the bottom quartile by median income, 20% came from the second quartile, 25% from the third quartile and 42% from the top quartile. No significant differences were found in baseline quality of life scores between insurance groups or income quartiles. Patients with both private and public insurance had higher baseline fatigue scores compared to only private, only public, or other insurance. No significant difference was found in baseline fatigue scores by income quartile. No significant differences were found in overall survival by insurance group or income quartile. Conclusions: Patients with both private and public insurance may need more extensive interventions than patients with other insurance statuses due to their higher baseline fatigue scores. Future studies are needed to further investigate the effects of neighborhood advantage level on quality of life indicators.

ContributorsPetersen, Emma K. (Author) / Ross, Heather (Thesis director) / Dueck, Amylou (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2021-12