Department of Statistics and Actuarial Science, Northern Illinois University, DeKalb, IL, USA.
Department of Statistics, University of South Carolina, Columbia, SC, USA.
Biom J. 2020 Nov;62(7):1791-1809. doi: 10.1002/bimj.202000039. Epub 2020 Jun 22.
We propose new parametric frameworks of regression analysis with the conditional mode of a bounded response as the focal point of interest. Covariate effects estimation and prediction based on the maximum likelihood method under two new classes of regression models are demonstrated. We also develop graphical and numerical diagnostic tools to detect various sources of model misspecification. Predictions based on different central tendency measures inferred using various regression models are compared using synthetic data in simulations. Finally, we conduct regression analysis for data from the Alzheimer's Disease Neuroimaging Initiative to demonstrate practical implementation of the proposed methods. Supporting Information that contain technical details and additional simulation and data analysis results are available online.
我们提出了新的参数回归分析框架，以有界响应的条件模式为关注焦点。在两种新的回归模型类别下，基于最大似然方法展示了协变量效应估计和预测。我们还开发了图形和数值诊断工具，以检测模型误设的各种来源。使用不同的回归模型推断的不同中心趋势度量的预测，使用模拟中的合成数据进行比较。最后，我们对来自阿尔茨海默病神经影像学倡议的数据进行回归分析，以展示所提出方法的实际应用。包含技术细节和附加模拟及数据分析结果的支持信息可在线获取。
