Department of Statistics, Sinop University.
Department of Methodology and Statistics, Utrecht University.
Psychol Methods. 2021 Oct;26(5):599-621. doi: 10.1037/met0000406.
In the social and behavioral sciences, it is often not interesting to evaluate the null hypothesis by means of a p-value. Researchers are often more interested in quantifying the evidence in the data (as opposed to using p-values) with respect to their own expectations represented by equality and/or inequality constrained hypotheses (as opposed to the null hypothesis). This article proposes an Akaike-type information criterion (AIC; Akaike, 1973, 1974) called the generalized order-restricted information criterion approximation (GORICA) that evaluates (in)equality constrained hypotheses under a very broad range of statistical models. The results of five simulation studies provide empirical evidence showing that the performance of the GORICA on selecting the best hypothesis out of a set of (in)equality constrained hypotheses is convincing. To illustrate the use of the GORICA, the expectations of researchers are investigated in a logistic regression, multilevel regression, and structural equation model. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
在社会和行为科学中，通过 p 值来评估零假设通常并不有趣。研究人员通常更感兴趣的是用数据中的证据来量化（而不是使用 p 值），这些证据是针对他们自己的期望的，这些期望由平等和/或不平等约束假设（而不是零假设）来表示。本文提出了一种 Akaike 型信息准则（AIC；Akaike，1973 年，1974 年），称为广义有序约束信息准则逼近（GORICA），该准则在非常广泛的统计模型下评估平等和不平等约束假设。五项模拟研究的结果提供了经验证据，表明 GORICA 在从一组（平等和不平等）约束假设中选择最佳假设方面的性能令人信服。为了说明 GORICA 的使用，在逻辑回归、多层次回归和结构方程模型中研究了研究人员的期望。（PsycInfo 数据库记录（c）2021 APA，保留所有权利）。
