Motivated by the Iowa Fluoride Study (IFS) dataset, which comprises zero-inflated multi-level ordinal responses on tooth fluorosis, we develop an estimation scheme leveraging generalized estimating equations (GEEs) and James-Stein shrinkage. Previous analyses of this cohort study primarily focused on caries (count response) or employed a Bayesian approach to the ordinal fluorosis outcome. This study is based on the expanded dataset that now includes observations for age 23, whereas earlier works were restricted to ages 9, 13, and/or 17 according to the participants' ages at the time of measurement. The adoption of a frequentist perspective enhances the interpretability to a broader audience. Over a choice of several covariance structures, separate models are formulated for the presence (zero versus non-zero score) and severity (non-zero ordinal scores) of fluorosis, which are then integrated through shared regression parameters. This comprehensive framework effectively identifies risk or protective effects of dietary and non-dietary factors on dental fluorosis.

翻译：受爱荷华州氟化物研究（IFS）数据集启发——该数据集包含牙齿氟中毒的零膨胀多水平有序响应——我们开发了一种利用广义估计方程（GEEs）和James-Stein收缩的估计方案。先前对这一队列研究的分析主要关注龋齿（计数响应）或对有序氟中毒结果采用贝叶斯方法。本研究基于扩展后的数据集，该数据集现已包含23岁时的观测值，而早期研究根据参与者测量时的年龄仅局限于9岁、13岁和/或17岁。采用频率学派的视角增强了对更广泛受众的可解释性。在多种协方差结构的选择下，我们分别针对氟中毒的存在性（零分与非零分）和严重程度（非零有序分数）建立了模型，然后通过共享的回归参数将其整合。这一综合框架有效地识别了饮食与非饮食因素对牙氟中毒的风险或保护效应。