DEVELOP METHODOLOGY FOR COMPLEX SAMPLE SURVEYS--PHASE II

EIFACS将使流行病学家和其他研究人员能够进行有效的 复杂抽样设计调查数据的多元分析 可视化用户界面PC环境。调查数据可以是字符 形式或在特殊的包生成的数据集中（例如，SAS）和 本地存储或连接的工作站或大型机（远程 执行）。程序包括：加权kappa，四重表（fft）， 分层FFT，判别分析，多分类逻辑回归， 结构方程建模和比例风险生存 分析.通过泰勒级数线性化或 愤怒允许所有实际抽样设计规范。 此外，还为SUDAAN（另一个复杂的调查）提供了一个接口 软件包），该软件包使EIFACS定义的数据能够以可视方式设置， 外国处决这一努力将在早期开发的IFACS的基础上进行扩展 系统，体现了同样的理念。研究计划包括： 需求更新，软件功能规范，新的和增强的 程序开发（算法、代码、阿尔法测试、蒙特卡罗 模拟）、用户界面改进、预分析增强 （转换/重新编码、缺失值插补等），远程 执行优化、beta测试、文档编制和最终安装 在NIAAA。

EIFACS will enable epidemiologists and other researchers to perform valid multivariate analyses on complex-sampling-design survey data within a visual user-interface PC environment. The survey data may be in character form or in special package-generated data sets (e.g., SAS) and either locally stored or at a connected workstation or mainframe (remote execution). Procedures include: weighted kappa, fourfold tables (fft), stratified fft, discriminant analysis, polytomous logistic regression, structural equations modeling, and proportional hazards survival analysis. Variances are estimated by Taylor series linearization or resampling. All practical sampling design specifications are permitted. Additionally, an interface is provided to SUDAAN (another complex survey package) which enables EIFACS defined data to be visually set up for foreign execution. This effort will expand on the earlier developed IFACS system which embodies the same concept. The research plan includes: requirements update, software functional specification, new and augmented procedures development (algorithms, code, alpha-test, Monte Carlo simulation), user-interface improvement, pre-analysis augmentation (transformation/recoding, missing value imputation, etc.), remote execution refinement, beta testing, documentation, and final installation at NIAAA.