Institute on Statistical Analysis: Causal Analysis Using International Data
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AERA Institute on Statistical Analysis for Education Policy:
Causal Analysis Using International Data

Call for Applications

Dates of Institute: May 6-9, 2014

The deadline to apply to the 2014 AERA Institute on Statistical Analysis for Education Policy: Causal Analysis Using International Data has passed. Please continue to check the AERA Grants Program webpage for future professional development opportunities.

With support from the National Science Foundation (NSF), the AERA Grants Program announces a special AERA Institute on Statistical Analysis for Education Policy focused on Causal Analysis using data from two international datasets, Trends in International Mathematics and Science Study (TIMSS) and Programme for International Student Assessment (PISA). The Institute’s goal is to help develop a critical mass of U.S. educational researchers using NCES and NSF data sets for basic, policy, and applied research. The Institute will be conducted jointly with an international of group scholars from other countries.


Causal inference has become a central issue in educational research. This includes inferring causality from the design of true randomized experiments, as well as how such inference can be approached in quasi-experimental, non-randomized studies. The focus of the 2014 Institute will be on these issues and the methodologies available to support causal inferences using data from TIMSS and PISA. The Institute will cover several approaches and methodologies for estimating causal inferences using TIMSS and PISA. Such methodologies include propensity scores, path analysis, and structural equation models. During the Institute examples will be provided in addition to working sessions in which participants will gain experience with implementing selected methods with the international data.

Eligibility and Review Criteria

Advanced doctoral students and recent doctorates are especially encouraged to apply. Applicants must have completed at least one year of statistics courses at the doctoral level and have familiarity with multiple regression methods. Review criteria include: the applicant’s statistical background to at least the intermediate level of multiple regression, computer literacy with knowledge of at least one statistical software package; experience in using a large-scale data set; substantive policy or practice interest in international data; and the Institute’s fit with the applicant’s career goals. Applications from historically underrepresented minority scholars are also strongly encouraged. Applicants may be U.S. citizens, U.S. permanent residents, or non-U.S. citizens working or studying at a U.S. institution.

Participant Support

A select group of scholars will be chosen to participate in the Institute. Those selected for participation will receive support covering the Institute's fees, transportation, housing, and meals for the dates of the Institute. Participants must bring their own computer loaded with the statistical software of their choice.

Dates and Location

May 6-9, 2014, in Washington, DC

Institute Director
William Schmidt, Michigan State University

Application Requirements
All applications should include:

  • Background Information, entered via the online submission tool, including contact information for three (3) references familiar with the applicant’s work. No letters of recommendation are required for this application, although references may be contacted during the review process.

  • Statement of Interest in PDF (maximum two pages single-spaced), describing the applicant's background, career goals, and how the applicant would benefit from the Institute.

  • Summarized Curriculum Vita in PDF (maximum one page), listing education, research, and employment history, relevant graduate courses, and publications that are relevant to the Institute.

Application Submission

The deadline for applications to attend the 2014 Institute on Statistical Analysis has passed. Applicants will be informed of decisions in March 2014. If you have any questions, please contact Kevin Dieterle at or 202-238-3227.

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