A Summer Workshop on the Analysis of Longitudinal Study of American Youth (LSAY) Data

目前的项目将支持一个培训讲习班的纵向研究美国青年（LSAY）的数据集的高级研究生，早期职业学者，和其他感兴趣的研究人员。自1987年以来，LSAY一直跟踪7年级和10年级公立学校学生的全国概率样本，是运行时间最长，最全面的数据集，可用于检查有助于学生和年轻人对科学，技术，工程，数学和医学的兴趣和理解的因素。LSAY在二十多年来对家庭、学校、同伴和社区变量的测量方面与众不同，这使得它成为寻求理解这些因素之间相互作用的分析的理想工具。LSAY数据集的全面性和纵向性可能会给不熟悉LSAY的研究人员带来挑战，例如计量的广度和适合于分析随时间变化的具体统计程序。为了解决这个问题，该项目将招募20名研究人员参加由密歇根大学政治和社会研究校际联盟（ICPSR）主办的为期5天的研讨会。 主题将包括：（1）对LSAY数据集结构的介绍;（2）参与者在科学和数学方面的成就，包括这些测量的心理测量学基础;（3）LSAY中许多开放式项目的编码;（4）地理和位置数据的存在和使用;（5）重复纵向研究中的测量误差，以及解决这些误差的适当方法。

The present project will support a training workshop on the Longitudinal Study of American Youth (LSAY) data set for advanced graduate students, early career scholars, and other interested researchers. Since 1987, LSAY has followed a national probability sample of 7th and 10th grade public school students, and is the longest-running and most comprehensive data set available to examine the factors that contribute to student and young adult interest in and understanding of science, technology, engineering, mathematics, and medicine. The LSAY is distinctive in its measurement of home, school, peer, and community variables over more than two decades, making it ideal for analyses that seek to understand the interaction between and among these factors.The comprehensive and longitudinal nature of the LSAY data set can present challenges to researchers unfamiliar with LSAY, such as the breadth of measures and the particular statistical procedures appropriate for analyses of change over time. To address this, this project will recruit 20 researchers for a 5-day workshop, hosted by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan. Topics will include: (1) an introduction to the structure of the LSAY data set; (2) participants' achievement in science and mathematics, including the psychometric basis for these measures; (3) the coding of the many open-ended items in the LSAY; (4) the presence and use of geographic and location data; (5) measurement errors in repeated, longitudinal studies, and appropriate methods to address such errors.