Common random effects models for repeated measurements account for the heterogeneity in the population by including subject-specific intercepts or variable effects. They do not account for the heterogeneity in answering tendencies. For ordinal responses in particular, the tendency to choose extreme or middle responses can vary in the population. Extended models are proposed that account for this type of heterogeneity. Location effects as well as the tendency to extreme or middle responses are modelled as functions of explanatory variables. It is demonstrated that ignoring response styles may affect the accuracy of parameter estimates. An example demonstrates the applicability of the method.

用于重复测量的常见随机效应模型通过包括特定于受试者的拦截或变量效应来解决总体中的异质性。他们没有考虑回答倾向中的异质性。特别是对于顺序反应，在人群中选择极端或中等反应的趋势可能会有所不同。提出了扩展模型来说明这种类型的异质性。位置效应以及极端或中间响应的趋势被建模为解释变量的函数。事实证明，忽略响应样式可能会影响参数估计的准确性。一个例子说明了该方法的适用性。