We are offering these pre-conference workshops which will run on the Thursday morning March 21, 2019 from 8:30-11:30.
Education Data Portal
High quality, accessible data are necessary for education policy analysts to effectively drive evidence-based decision-making. Although analysts have begun to harness the vast array of education-related data that is publicly available, the difficulty in accessing these data and converting them into actionable information has slowed progress.
To address this problem, the Urban Institute built the Education Data Portal, which makes K-12 and higher education data easily accessible to the public. We are bringing all major national datasets on schools, districts, and colleges under one roof and standardizing the information and data documentation so that it is easy to access data, measure change over time, and make connections across datasets. Data are currently available to download directly or access through an API and Stata/R packages, and will soon be made available through a point-and-click online interface.
Matthew Chingos and Erica Blom will provide an overview of the Education Data Portal and lead a hands-on training on how to use these new data tools. Participants should bring a laptop computer with their statistical software of choice (the training will focus on accessing the Portal through direct download and the Stata package, but will also briefly cover the R package). Sponsorship covers the cost of this workshop, but participants do need to register/RSVP.
What would it take to Change your Inference? Quantifying the Discourse about Causal Inferences in the Social Sciences
Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding variables or non-random selection into a sample. We will answer the question about what it would take to change an inference by formalizing the sources of bias and quantifying the discourse about causal inferences in terms of those sources. For example, we will transform challenges such as “But the inference of a treatment effect might not be valid because of pre-existing differences between the treatment groups” to questions such as “How much bias must there have been due to uncontrolled pre-existing differences to make the inference invalid?” “QQQ% of the cases would have to be replaced with cases with no treatment effect to change the inference.”
In part I we will use Rubin’s causal model to interpret how much bias there must be to invalidate an inference in terms of replacing observed cases with counterfactual cases or cases from an unsampled population. In part II, we will quantify the robustness of causal inferences in terms of correlations associated with unobserved variables or in unsampled populations. Calculations for bivariate and multivariate analysis will be presented using an app: http://konfound-it.com as well as macros in STATA and R and a spreadsheet for calculating indices [KonFound-it!].
The format will be a mixture of presentation, individual exploration, and group work. Participants may include graduate students and professors, although all must be comfortable with basic regression and multiple regression. Participants should bring their own laptop, or be willing to work with another student who has a laptop. Participants may choose to bring to the course an example of an inference from a published study or their own work, as well as data analyses they are currently conducting.
The workshop will be provided by Ken Frank MSU Foundation Professor of Sociometrics in Measurement and Quantitative Methods at Michigan State University in Counseling, Educational Psychology and Special Education.
Accessing and Exploring NCES Data
The National Center for Education Statistics (NCES) has several state-of-the-art data tools that allow users to easily access and analyze data. This workshop provides participants with a comprehensive overview of those tools to access data sets. Participants will learn how to access public-use and restricted-use data sets, create reports and data tables, find published reports and conduct analyses in selected statistical tools. NCES offers a large variety of national, state, local, school and student data sets including assessment data, cross sectional data, survey data and administrative records, and participants will better understand which data sets cover their educational topic of interest.
The workshop is designed for graduate students, faculty members, researchers and other users with interest in using NCES data for their research studies, evaluations, and data projects. Participants are not required to have any pre-requisite skills to attend, and should bring their personal laptops for interactive, in-class activities. Each participant will receive an Accessing and Exploring NCES Data “cookbook,” that provides comprehensive instruction and screen shots explaining how to navigate a myriad of NCES data tools and the DLDT.
The workshop will introduce NCES’ Distance Learning Dataset Training System (DLDT). The workshop will also offer an in-depth instruction on four NCES data tools, including the Elementary/Secondary Information System (ELSI); the National Assessment of Educational Progress (NAEP) Data Explorer; Educational Demographic and Geographic Estimates (EDGE) data tools to explore ACS and GIS data; and the new Integrated Postsecondary Education Data System (IPEDS).