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A Study on Testing and Improving Nonlinear Evaluation Methods for Academic Journals

机译:检验和改进学术期刊非线性评价方法的研究

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In this paper, indicator-based comprehensive evaluation methods for academic journals are divided into two groups: linear and nonlinear evaluation methods. In nonlinear evaluation, sometimes an abnormal phenomenon occurs where the final evaluation score decreases while the value of component indicators increases. Regression adjustment method, a new method for test and improvement, is suggested as a solution for the above abnormality. In regression adjustment method the first step is a multicollinearity test after a regression analysis, where evaluation score is used as dependent variable and evaluation indicators as independent variables; the second step is to judge whether multicollinearity occurs or not. In the case of no multicollinearity, one should give up those indicators with negative regression coefficients, and then renew the previous process if there is multicollinearity, however, one should adopt ridge regression approach for estimation and adjustment. The authors conclude that attention should be paid to hidden defects in nonlinear evaluation methods; prudence is necessary before one decides to give up certain indicators; excessive regression-adjustment circles is not recommended; there may be nonlinear evaluation methods free from the requirements for test and improvement; further study is expected on many issues in journal evaluation methods.
机译:本文将基于指标的学术期刊综合评价方法分为线性评价方法和非线性评价方法两类。在非线性评估中,有时会出现异常现象,其中最终评估分数降低而组件指标的值增加。为了解决上述异常,建议使用回归调整法作为一种测试和改进的新方法。在回归调整方法中,第一步是经过回归分析后的多重共线性检验,其中评估得分用作因变量,评估指标用作自变量。第二步是判断是否存在多重共线性。在没有多重共线性的情况下,应该放弃那些具有负回归系数的指标,然后在存在多重共线性的情况下更新先前的过程,但是,应该采用岭回归方法进行估计和调整。作者得出结论,在非线性评估方法中应注意隐藏的缺陷。在决定放弃某些指标之前,必须谨慎行事;不建议使用过多的回归调整圈;可能存在不受测试和改进要求约束的非线性评估方法;期望在期刊评估方法中的许多问题上进行进一步研究。

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