Maximizing the Head Start Impact Study: New Third Grade Follow-up Data, Contextual Variables, and Approaches To Understanding Variation In Impacts
- Camilla Heid, Westat, Inc.
- Ronna Cook, Ronna Cook Associates
- Christina Weiland, University of Michigan
- Dana Charles McCoy, Harvard University
- Maia Connors, New York University
- Johanna Bleckman, ICPSR
Deadline: The application deadline has been extended to Thursday, June 5.
The Head Start Impact Study is a large, longitudinal, nationally representative study of the Head Start Population, aimed at determining how Head Start affects their school readiness. Join us for a fresh look at this significant dataset, including discussion of new methodology for better understanding impacts, and new variables that allow for contextual analysis and follow-up of children through third grade. Participants will have time to work on-site with all of the available data, with the instructors providing guidance and support.
Head Start Impact Study and Third Grade Follow-up Data
Dr. Camilla Heid, Westat and Ms. Ronna Cook, Ronna Cook Associates, will lead a session providing an overview of the study purpose, methods, and key findings for the HSIS and the subsequent Third Grade Follow-up. The presentation will include a discussion of the sample selection and random assignment, instruments, analysis, basic weights, data files and tips for using the datasets.
New Analysis Method: Impact Variation
Dr. Christina Weiland, University of Michigan, will lead a session on detecting and quantifying variation in the effects of assignment to Head Start. She will cover the conceptual framework and statistical principles behind this new and evolving methodology. And, she will also present findings on variation in the impacts of Head Start assignment.
Added Variables: Neighborhood Data
Dr. Dana McCoy, Harvard University and Ms. Maia Connors, New York University will lead a session on the new publicly available neighborhood data associated with the HSIS. This session will cover the origins of the neighborhood data, descriptions of key variables, and tips for matching the data with centers and center groups. The instructors will also present their own work as examples of how the neighborhood data can be applied.
Tips and Tricks
Dr. Weiland, Dr. McCoy, and Ms. Connors, will lead a session on tips, tricks, and lessons learned in using the HSIS data. This session will deepen participants' understanding of particularly challenging and complex aspects of these data. The session will cover a variety of topics including decisions regarding the use of sampling weights, measures of classroom quality, and choosing among similar variables. Participants will have the opportunity to explore some of these issues and familiarize themselves with the data in hands-on practice sessions.
Prerequisites: Participants are expected to have a basic understanding of secondary data, fundamental data analysis skills including multilevel modeling, knowledge of SPSS, SAS, or Stata, and a substantive interest in early care and education. Please include in your cover letter a description of any prior experience with the HSIS.
Application: Admission is competitive and limited to 25 participants. Apply using the Summer Program portal (by clicking on the "Registration & Fees" tab at the top of this page) to provide your information, select the course, and complete the section on your quantitative/statistical experience. Also, upload the following documents via the portal:
- Current curriculum vita
- Cover letter summarizing research interests and experiences
Stipends: Admitted graduate students, post-doctoral scholars, and junior faculty/researchers will be considered for one of a limited number of stipends to help with travel and housing costs. To be considered for one of these awards, applicants must also submit a letter of support from a senior faculty member, mentor, or adviser.
Fee: There are no tuition fees for accepted participants.
Tags: Head Start
Location: ICPSR -- Ann Arbor, MI
Date(s): July 16 - July 18
Time: 9:00 AM - 5:00 PM