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首页> 外文期刊>International Journal of Finance and Accounting >The Importance of the Effect of Exogenous Interaction Factors on Endogenous Variables in Accounting Modeling
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The Importance of the Effect of Exogenous Interaction Factors on Endogenous Variables in Accounting Modeling

机译：在会计建模中，外在相互作用因素对内在变量影响的重要性

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Most researchers in accounting use models having dummy independent variables to divide the research objects into two or more groups of objects or individuals. In other researches, they employ more than one variable in the model. However, the dummy variable(s) that stand alone may implicate improper correlations between the numerical independent variables with the corresponding dependent variable within the groups, namely the numerical independent variables have the same effects on the dependent variables within all groups of individuals. To overcome this problem, interaction factors between the dummies and the numerical variable(s) should be used as additional independent variables. So that the models considered would be heterogeneous regression models. It is found, only very few researchers employ the heterogeneous regression models, or the interaction models in general, in top accounting journal, recently. This paper attempts to show that the absence of interaction models may mislead the causal relationship between the independent and dependent variables, specifically between the numerical variables, of the models. The main objective of this paper is to present the importance of interaction models should be applied as the basic statistical models. It is expected that this paper can contribute for a better understanding to the students and less experience researchers in developing the statistical models, in various field of studies.
机译：会计学中的大多数研究人员使用具有虚拟自变量的模型将研究对象分为两组或更多组对象或个人。在其他研究中，他们在模型中采用了多个变量。但是，单独的虚拟变量可能会暗示数字自变量与组内相应因变量之间的不正确相关性，即数字自变量对所有个体组内的因变量具有相同影响。为了克服这个问题，假人和数值变量之间的相互作用因子应被用作附加的自变量。这样所考虑的模型将是异构回归模型。最近在顶级会计杂志上发现，只有极少数的研究人员采用异构回归模型或一般的交互模型。本文试图表明，缺少交互模型可能会误导模型的自变量和因变量之间，尤其是数值变量之间的因果关系。本文的主要目的是介绍交互模型的重要性，应将其用作基本统计模型。期望本文可以在研究的各个领域为学生和较少经验的研究人员提供更好的理解，帮助他们开发统计模型。

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