MODEL CHECKING FOR BIOMEDICAL DATA

统计分析得出的结论在很大程度上取决于 拟合模型的有效性。因此，对充分性的仔细检查 应该始终是任何统计推断的一部分 程序。目前还没有商业套餐提供 一种检查大类回归模型不适合性的统一方法。 这项建议旨在满足这一需求。它的目标是发展 将测试模型错误规范的商业软件 具有或不具有相关误差项的广义线性模型 线性回归模型、COX比例风险模型和 各种半参数和参数生存模型。该方法 基于对观测数据的累积残差和进行比较 到假设条件下通过模拟获得的相应累计金额 模特。它结合了图形和数值模型检查 程序。尽管该软件依赖于相当高级的数学 用户可以通过友好和灵活的 在熟悉的Windows-95平台上运行的用户界面。此用户 界面充分利用了动态图形，并鼓励交互 选型、装配、校核。该软件将可用 作为独立的Windows实施，作为外部SAS程序， 并作为外部sPlus函数。 建议的商业应用： 商业包中几乎没有软件可以用来检查 广义线性模型的模型假设的充分性， 非线性模型和生存模型。然而，这些模型仍在使用 广泛用于生物医学、经济和管理应用。一个 同时实现模型拟合和模型试验的软件包 灵活的交互式Windows环境中的过程应具有 巨大的商业吸引力。

The conclusions from a statistical analysis depend heavily on the validity of the fitted model. Thus a careful examination of the adequacy of the model should always be a part of any statistical inference procedure. There is at present no commercial package that provides a unified way to check lack-of-fit for a broad class of regression models. This proposal is intended to fill that need. Its goal is to develop commercial software which will test for model mis-specification of generalized linear models with or without correlated error terms, non- linear regression models, the Cox proportional hazards model, and a variety of semi-parametric and parametric survival models. The approach is based on comparing cumulative sums of residuals for the observed data to corresponding cumulative sums obtained by simulation under the assumed model. It incorporates both graphical and numerical model checking procedures. Although the software relies on fairly advanced mathematics the user is shielded from these complexities by a friendly and flexible user interface running on the familiar Windows-95 platform. This user interface makes good use of dynamic graphics and encourages interactive model selection, fitting and checking. The software will be available as a stand-alone Windows implementation, as an external SAS procedure, and as an external Splus function. PROPOSED COMMERCIAL APPLICATIONS: Very little software is available in commercial packages for checking the adequacy of the model assumptions for generalized linear models, nonlinear models and survival models. Yet these models are used extensively for biomedical, economic, and managerial applications. A software package implementing both model fitting and model testing procedures in a flexible interactive Windows environment should have great commercial appeal.