التفاصيل البيبلوغرافية
| العنوان: |
Technical Background for 'A Precision Medicine Approach to Develop and Internally Validate Optimal Exercise and Weight Loss Treatments for Overweight and Obese Adults with Knee Osteoarthritis' |
| المؤلفون: |
Jiang, Xiaotong, Nelson, Amanda E., Cleveland, Rebecca J., Beavers, Daniel P., Schwartz, Todd A., Arbeeva, Liubov, Alvarez, Carolina, Callahan, Leigh F., Messier, Stephen, Loeser, Richard, Kosorok, Michael R. |
| سنة النشر: |
2020 |
| المجموعة: |
ArXiv.org (Cornell University Library) |
| مصطلحات موضوعية: |
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications |
| الوصف: |
We provide additional statistical background for the methodology developed in the clinical analysis of knee osteoarthritis in "A Precision Medicine Approach to Develop and Internally Validate Optimal Exercise and Weight Loss Treatments for Overweight and Obese Adults with Knee Osteoarthritis" (Jiang et al. 2020). Jiang et al. 2020 proposed a pipeline to learn optimal treatment rules with precision medicine models and compared them with zero-order models with a Z-test. The model performance was based on value functions, a scalar that predicts the future reward of each decision rule. The jackknife (i.e., leave-one-out cross validation) method was applied to estimate the value function and its variance of several outcomes in IDEA. IDEA is a randomized clinical trial studying three interventions (exercise (E), dietary weight loss (D), and D+E) on overweight and obese participants with knee osteoarthritis. In this report, we expand the discussion and justification with additional statistical background. We elaborate more on the background of precision medicine, the derivation of the jackknife estimator of value function and its estimated variance, the consistency property of jackknife estimator, as well as additional simulation results that reflect more of the performance of jackknife estimators. We recommend reading Jiang et al. 2020 for clinical application and interpretation of the optimal ITR of knee osteoarthritis as well as the overall understanding of the pipeline and recommend using this article to understand the underlying statistical derivation and methodology. |
| نوع الوثيقة: |
text |
| اللغة: |
unknown |
| العلاقة: |
http://arxiv.org/abs/2001.09930Test |
| الإتاحة: |
http://arxiv.org/abs/2001.09930Test |
| رقم الانضمام: |
edsbas.28C72188 |
| قاعدة البيانات: |
BASE |
