期刊
NATURE NEUROSCIENCE
卷 17, 期 4, 页码 491-496出版社
NATURE PORTFOLIO
DOI: 10.1038/nn.3648
关键词
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资金
- European Union (ERC Advanced grant) [322966, HEALTH-F2-2009-241498 EUROSPIN, HEALTH-F2-2009-242167 SynSys]
- Netherlands Organization for Scientific Research [TOP 903-42-095]
- European Research Council (Genetics of Mental Illness) [ERC-230374]
- Netherlands Scientific Organization (Nederlandse Organisatie voor Wetenschappelijk Onderzoek, gebied Maatschappij-en Gedragswetenschappen: NWO/MaGW) [VIDI-452-12-014]
In neuroscience, experimental designs in which multiple observations are collected from a single research object (for example, multiple neurons from one animal) are common: 53% of 314 reviewed papers from five renowned journals included this type of data. These so-called 'nested designs' yield data that cannot be considered to be independent, and so violate the independency assumption of conventional statistical methods such as the t test. Ignoring this dependency results in a probability of incorrectly concluding that an effect is statistically significant that is far higher (up to 80%) than the nominal a level (usually set at 5%). We discuss the factors affecting the type I error rate and the statistical power in nested data, methods that accommodate dependency between observations and ways to determine the optimal study design when data are nested. Notably, optimization of experimental designs nearly always concerns collection of more truly independent observations, rather than more observations from one research object.
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