Formann A K
Department of Psychology, University of Vienna, Austria.
Biometrics. 1994 Sep;50(3):865-71.
Latent class models have been proposed for assessing relative errors in discrete measurements arising, for example, in caries diagnosis. Those models, however, that turned out to fit empirical data (N = 3,869 teeth, 5 dentists) to a sufficient degree, needed the inclusion of interaction terms for pairs of raters at the latent levels in order to describe the observed interrelations of the judgments. Now it is shown that instead of giving up the concept of local stochastic independence, increasing the number of classes while possibly restricting their parameters in the end has the same effect: Both the unrestricted three-class model, which can be interpreted to be the generalization of the Carlos-Senning assumptions, and a restricted four-class model, which resembles the latent distance model well known from psychometrics, give good and excellent fit, respectively, to the caries data. For the case of the four-class model, a second solution exists that exhibits exactly the same fit, giving rise to warnings against the possibility of multiple solutions to the likelihood equations.
潜类别模型已被提出用于评估离散测量中的相对误差，例如在龋齿诊断中出现的误差。然而，那些被证明能充分拟合经验数据（N = 3869颗牙齿，5名牙医）的模型，需要在潜水平上纳入评分者对的交互项，以描述观察到的判断之间的相互关系。现在表明，与其放弃局部随机独立性的概念，增加类别数量同时最终可能限制其参数会有相同的效果：无限制的三类模型（可解释为卡洛斯 - 森宁假设的推广）和受限的四类模型（与心理测量学中熟知的潜距离模型非常相似）分别对龋齿数据给出了良好和出色的拟合。对于四类模型的情况，存在第二种解，其拟合效果完全相同，这引发了对似然方程可能存在多个解的警告。
