An AIC-type information criterion evaluating theory-based hypotheses for contingency tables.

IF 4.6 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Yasin Altinisik, Roy S Hessels, Caspar J Van Lissa, Rebecca M Kuiper
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引用次数: 0

Abstract

Researchers face inevitable difficulties when evaluating theory-based hypotheses in the context of contingency tables. Log-linear models are often insufficient to evaluate such hypotheses, as they do not provide enough information on complex relationships between cell probabilities in many real-life applications. These models are usually used to evaluate the relationships between variables using only equality restrictions between model parameters, while specifying theory-based hypotheses often also requires inequality restrictions. Moreover, high-dimensional contingency tables generally contain low cell counts and/or empty cells, complicating parameter estimation in log-linear models. The presence of many parameters in these models also causes difficulties in interpretation when evaluating the hypotheses of interest. This study proposes a method that simplifies evaluating theory-based hypotheses for high-dimensional contingency tables by simultaneously addressing each of the above problems. With this method, theory-based hypotheses, which are specified using equality and/or inequality constraints with respect to (functions of) cell probabilities, are evaluated using an AIC-type information criterion, GORICA. We conduct a simulation study to evaluate the performance of GORICA in the context of contingency tables. Two empirical examples illustrate the use of the method.

一种aic型信息准则,评价列联表中基于理论的假设。
在列联表的背景下,研究人员在评估基于理论的假设时面临着不可避免的困难。对数线性模型通常不足以评估这样的假设,因为在许多实际应用中,它们不能提供足够的关于细胞概率之间复杂关系的信息。这些模型通常只使用模型参数之间的等式限制来评估变量之间的关系,而指定基于理论的假设通常也需要不等式限制。此外,高维列联表通常包含低单元计数和/或空单元,使对数线性模型中的参数估计复杂化。在评估感兴趣的假设时,这些模型中许多参数的存在也会导致解释困难。本研究提出了一种方法,通过同时解决上述每个问题,简化了对高维列联表基于理论的假设的评估。通过这种方法,使用aic类型的信息准则GORICA来评估基于理论的假设,这些假设使用关于单元概率(函数)的等式和/或不等式约束来指定。我们进行了模拟研究,以评估在列联表背景下GORICA的性能。两个实例说明了该方法的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.30
自引率
9.30%
发文量
266
期刊介绍: Behavior Research Methods publishes articles concerned with the methods, techniques, and instrumentation of research in experimental psychology. The journal focuses particularly on the use of computer technology in psychological research. An annual special issue is devoted to this field.
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