Core--Management and methods facility

拟议的人口老龄化全球疾病负担方案项目的核心将在行政、数据和方法需求方面协调八个研究小组的活动方面发挥核心作用。该中心将设在哈佛人口与发展研究中心的哈佛疾病负担部门，将有三个主要功能。首先，核心的行政部分将通过以下方式为八个研究项目提供支持：促进项目负责人之间的互动，鼓励项目调查人员与世界卫生组织从事相关问题工作的公共卫生专业人员之间的交流，编写和协调报告和出版物，编写和协调方案报告和出版物，以及监督整个方案预算。其次，核心的数据组件将使用哈佛-麻省理工学院数据中心开发的原型和软件创建一个全球数据库。全球数据库将包含本项目收集、分析、生成和使用的所有数据，以及将在本项目过程中开发的软件包。所有互联网用户都可以访问全球数据库，但其中的一些部分将被招募。该数据库还将通过哈佛大学和麻省理工学院虚拟数据中心正在开发的软件，与其他具有社会经济、人口和健康数据的全球数据库“虚拟地”连接起来。第三，包括一个方法组件，用于开发、调整和改进统计方法，这将对程序的每个组件都有用。该方法核心将开发一种用于处理缺失数据的多重输入方法，以及一种基于模拟的方法，以一种实质性有意义的方式改进结果的呈现，包括不确定范围。这两种方法都将被开发成软件包，通过互联网广泛提供。

The core of the proposed Program Project on The Global Burden of Disease in Aging population will play a central role in coordinating the activities of the eight research teams, in terms of administrative, data and methodological needs. The core will be based at the Harvard Burden of Disease Unit at the Harvard Center for Population and Development Studies and will have three main functions. First, the administrative component of the core will provide support to the eight research projects by facilitating interactions between the project leaders, encouraging exchanges between the investigators in the program and public health professionals working on related issues at the World Health Organization, preparing and coordinating reports and publications, preparing and coordinating program reports and publications, and overseeing the overall program budget. Second, the data component of the core will create a Global Databank, using the prototype and software developed by Harvard-MIT Data Center. The Global Databank will contain all data collected, analyzed, generated, and used by this program, as well as the software packages that will be developed in the course of the program. All internet users will have access to the Global Databank but some parts of it will have recruited aces. The Databank will also be connected "virtually", through software in development of the Virtual Data Center at Harvard and MIT, to other global databanks with socioeconomic, demographic and health data. Third, the include a methods component for the development, adaptation, and refinement of statistical methods that will be useful to every component of the program. The methods core will develop a multiple imputation method for dealing with missing data, and a method based on simulation for improving the presentation of results in a substantively meaningful way, including ranges of uncertainty. Both of these methods will be developed into software packages that will be widely available for use through the internet.