Department of Psychology, University of Tartu Tartu, Estonia ; Estonian Academy of Sciences Tallinn, Estonia.
Front Psychol. 2014 May 9;5:371. doi: 10.3389/fpsyg.2014.00371. eCollection 2014.
Personality measurement is based on the idea that values on an unobservable latent variable determine the distribution of answers on a manifest response scale. Typically, it is assumed in the Item Response Theory (IRT) that latent variables are related to the observed responses through continuous normal or logistic functions, determining the probability with which one of the ordered response alternatives on a Likert-scale item is chosen. Based on an analysis of 1731 self- and other-rated responses on the 240 NEO PI-3 questionnaire items, it was proposed that a viable alternative is a finite number of latent events which are related to manifest responses through a binomial function which has only one parameter-the probability with which a given statement is approved. For the majority of items, the best fit was obtained with a mixed-binomial distribution, which assumes two different subpopulations who endorse items with two different probabilities. It was shown that the fit of the binomial IRT model can be improved by assuming that about 10% of random noise is contained in the answers and by taking into account response biases toward one of the response categories. It was concluded that the binomial response model for the measurement of personality traits may be a workable alternative to the more habitual normal and logistic IRT models.
人格测量基于这样一种观点，即不可观察的潜在变量上的价值观决定了显式反应量表上答案的分布。通常，在项目反应理论（IRT）中，假设潜在变量通过连续正态或逻辑函数与观察到的反应相关联，确定在李克特量表项目的有序反应选择之一被选择的概率。基于对 240 项 NEO PI-3 问卷项目的 1731 个自我和他人评定反应的分析，提出了一个可行的替代方案是有限数量的潜在事件，它们通过二项式函数与显式反应相关联，该函数只有一个参数-给定陈述被批准的概率。对于大多数项目，混合二项式分布的拟合效果最佳，该分布假设存在两个不同的子群体，他们以两个不同的概率认可项目。结果表明，通过假设大约 10%的随机噪声包含在答案中，并考虑对一个响应类别偏向的响应偏置，可以提高二项式 IRT 模型的拟合度。结论是，用于测量人格特质的二项式反应模型可能是更习惯的正态和逻辑 IRT 模型的可行替代方案。
