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Predictive power of statistical significance
A statistically significant research finding should not be defined as a P-value of 0.05 or less, because this definition does not take into account study power. Statistical significance was originally defined by Fisher RA as a P-value of 0.05 or less.
Thomas F Heston, Jackson King
openaire +3 more sources
This study demonstrates that KRAS and GNAS mutations are more prevalent in patients with resected intraductal papillary mucinous neoplasms (IPMN) compared to those under clinical surveillance. GNAS mutations significantly differ between the two patient cohorts, indicating that their absence may serve as a potential biomarker to support conservative ...
Christine Nitschke+12 more
wiley +1 more source
Abstract Background Ultrasonography (US) and 99mTechnetium‐sestamibi scintigraphy (99mTc‐MIBI) are currently first‐line imaging modalities to localize parathyroid adenomas with sensitivities of 80% and 84%, respectively. Therefore, finding other modalities to further improve the diagnostic accuracy for preoperative localization is critically needed ...
Fangyi Liu+7 more
wiley +1 more source
A Genetic Algorithm-based Framework for Learning Statistical Power Manifold [PDF]
Statistical power is a measure of the replicability of a categorical hypothesis test. Formally, it is the probability of detecting an effect, if there is a true effect present in the population. Hence, optimizing statistical power as a function of some parameters of a hypothesis test is desirable.
arxiv
Explorations in statistics: power
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fifth installment of Explorations in Statistics revisits power, a concept fundamental to the test of a null hypothesis. Power is the probability that we reject the null hypothesis when it is false. Four things affect power:
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We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić+31 more
wiley +1 more source
Treatment planning with a 2.5 MV photon beam for radiation therapy
Abstract Purpose The shallow depth of maximum dose and higher dose fall‐off gradient of a 2.5 MV beam along the central axis that is available for imaging on linear accelerators is investigated for treatment of shallow tumors and sparing the organs at risk (OARs) beyond it.
Navid Khaledi+5 more
wiley +1 more source
How to calculate statistical power for vegetation research [PDF]
Calculation of statistical power is important for proper interpretation of research results. Statistical Power depends on the selected significance level, sample size and effect size. Selection of an appropriate formula for calculating power of a test is
Mohammad Mousaei Sanjerehei
doaj
Fisher's combined probability test for high-dimensional covariance matrices [PDF]
Testing large covariance matrices is of fundamental importance in statistical analysis with high-dimensional data. In the past decade, three types of test statistics have been studied in the literature: quadratic form statistics, maximum form statistics, and their weighted combination.
arxiv
Measures of independence and functional dependence [PDF]
We follow up on Shi et al's (2020) and Cao's and my (2020) work on the local power of a new test for independence, Chatterjee (2019), and its relation to the local power properties of classical tests. We show quite generally that for testing independence with local alternatives either Chatterjee's rank test has no power, or it may be misleading: The ...
arxiv