Results 31 to 40 of about 3,789,491 (216)
Collabra: Psychology, 2021 An important step when designing an empirical study is to justify the sample size that will be collected. The key aim of a sample size justification for such studies is to explain how the collected data is expected to provide valuable information given the inferential goals of the researcher.
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Sample Size Considerations for Hierarchical Populations [PDF]
EFSA Journal, 2013 In applied sciences in general, and in particular when dealing with animal health and welfare assessments, one is often confronted with the collection of correlated data (not independent data).
European Food Safety Authority
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A systematic review of the “promising zone” design
Trials, 2020 Introduction Sample size calculations require assumptions regarding treatment response and variability. Incorrect assumptions can result in under- or overpowered trials, posing ethical concerns.
Julia M. Edwards +3 more
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High-low level support vector regression prediction approach (HL-SVR) for data modeling with input parameters of unequal sample sizes [PDF]
, 2019 Support vector regression (SVR) has been widely used to reduce the high computational cost of computer simulation. SVR assumes the input parameters have equal sample sizes, but unequal sample sizes are often encountered in engineering practices. To solve this issue, a new prediction approach based on SVR, namely as high-low-level SVR approach (HL-SVR ...
arxiv +1 more source
Sample size estimation in research: Necessity or compromise?
Kerala Journal of PsychiatryAn adequately powered sample is essential for accurate parameter estimation and meaningful significance testing. It is important to balance sample size with practical considerations such as cost and feasibility.
Samir Kumar Praharaj, Shahul Ameen
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Sample size calculations for indirect standardization
BMC Medical Research Methodology, 2023 Indirect standardization, and its associated parameter the standardized incidence ratio, is a commonly-used tool in hospital profiling for comparing the incidence of negative outcomes between an index hospital and a larger population of reference ...
Yifei Wang, Philip Chu
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Permutation-based group sequential analyses for cognitive neuroscience
NeuroImage, 2023 Cognitive neuroscientists have been grappling with two related experimental design problems. First, the complexity of neuroimaging data (e.g. often hundreds of thousands of correlated measurements) and analysis pipelines demands bespoke, non-parametric ...
John P. Veillette +2 more
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Epidemiology, Biostatistics and Public Health, 2023 The rate of phase III trials failures is approximately 42-45%, and most of them are due to a lack of efficacy. Some of the failures for a lack of efficacy are expected, due to type I errors in phase II and type II errors in phase III.
Daniele De Martini
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Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 1: Results from simulations with constant sample sizes [PDF]
arXiv, 2020 Contemporary statistical publications rely on simulation to evaluate performance of new methods and compare them with established methods. In the context of meta-analysis of log-odds-ratios, we investigate how the ways in which simulations are implemented affect such conclusions.
arxiv
Mesoscopic sensitivity of speckles in disordered nonlinear media to changes of disordered potential [PDF]
, 1999 We show that the sensitivity of wave speckle patterns in disordered nonlinear media to changes of scattering potential increases with sample size. For large enough sample size this quantity diverges, which implies that at given coherent wave incident on a sample there are multiple solutions for the spatial distribution of the wave's density. The number
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