V
Valen E. Johnson
Researcher at Texas A&M University
Publications - 160
Citations - 10887
Valen E. Johnson is an academic researcher from Texas A&M University. The author has contributed to research in topics: Bayesian probability & Bayes factor. The author has an hindex of 43, co-authored 155 publications receiving 9541 citations. Previous affiliations of Valen E. Johnson include University of North Carolina at Chapel Hill & Lanzhou University.
Papers
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Journal ArticleDOI
A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome.
Fan Gao,Fan Gao,Xuedong Pan,Xuedong Pan,Elissa B. Dodd-Eaton,Carlos Christian Vera Recio,Matthew D. Montierth,Matthew D. Montierth,Jasmina Bojadzieva,Phuong L. Mai,Kristin Zelley,Valen E. Johnson,Danielle Braun,Kim E. Nichols,Judy Garber,Sharon A. Savage,Louise C. Strong,Wenyi Wang +17 more
TL;DR: The developed Famdenovo to predict DNM status (DNM or familial mutation [FM]) of deleterious autosomal dominant germline mutations for any syndrome may serve as a foundation for future studies evaluating how new deleteriously mutations can be established in the germline, such as those in TP53.
Journal Article
A hierarchical model for estimating reliability from weapon system surveillance data
Journal ArticleDOI
Higher Stem Cell Dose Infusion As Rescue After Intensive Chemotherapy Does Not Improve Symptom Burden In Older Patients With Multiple Myeloma and Amyloidosis
Nina Shah,Loretta A. Williams,Audrey Worthing,Qiuling Shi,Xin Shelley Wang,Valen E. Johnson,Tito R. Mendoza,Muzaffar H. Qazilbash,Richard E. Champlin,Sergio Giralt,Charles S. Cleeland +10 more
TL;DR: Infusion of higher autologous stem cell dose after high dose chemotherapy does not yield a difference in engraftment time or symptom burden in the first few weeks after ASCT.
Posted Content
A Modified Sequential Probability Ratio Test
TL;DR: In this article, a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power is described.
Book ChapterDOI
Cancer Symptom Science: Bayesian adaptive design: a novel approach to test the effectiveness of symptom-reducing agents using patient-reported outcomes
Valen E. Johnson,Tito R. Mendoza +1 more
TL;DR: The lack of a strong clinical-trial evidence base for guiding symptom management practice for better symptom management, in cancer as well as in other diseases, has been hampered by the lack of evidence that would support rational use of both biological and behavioral interventions for symptom management as mentioned in this paper.