大蒜甲醇提取物对嗜水气单胞菌IC50值的四参数Logistic模型残差随机性检验

Rusnam, B. Gunasekaran, M. K. Sabullah
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引用次数: 0

摘要

许多出版物忽略了所使用的非线性模型的统计诊断,并且数据可能是非随机的-这对于所有参数统计评估方法都是必不可少的。如果诊断测试表明残差揭示了一种模式,那么各种补救措施(例如非参数分析或转移到另一个模型)应该可以解决问题。本研究的主题是使用wald -沃尔福威茨运行检验,对四参数Logistic模型残差的随机性进行检验,该模型用于获得大蒜甲醇提取物对嗜水气单胞菌的IC50值。结果表明,运行次数为10次,随机假设下的期望运行次数为5.8次,说明残差序列有足够的运行次数。由于p值大于0.05,因此没有拒绝原假设,表明没有实质性证据表明残差是非随机的,残差代表噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Test of Randomness of Residuals for the Four-parameter Logistic model used in Obtaining the IC50 Value for Allivum sativum Methanolic Extract Against Aeromonas hydrophila
Numerous publications ignore statistical diagnosing of the nonlinear model utilized, and the data might be nonrandom- an essential necessity for all of the parametric statistical evaluation approaches. In cases where the diagnostic tests demonstrate that the residuals reveal a pattern, then a variety of remedies for example nonparametric analysis or shifting to another model should cure the problem. The subject of this study is test for the randomness of the residual for the Four-parameter Logistic model used in obtaining the IC50 Value for Allivum sativum methanolic extract against Aeromonas hydrophila using the Wald–Wolfowitz runs test. The result shows that the number of runs was 10, the expected number of runs under the assumption of randomness was 5.8, indicating the series of residuals had adequate runs. As the p-value was greater than 0.05, the null hypothesis is not rejected demonstrating no substantial evidence that the residuals were nonrandom, and the residuals represent noise.
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