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IES Grant

Title: Proposal to Conduct Annual Workshops on Better Quasi-Experimental Design and Analysis
Center: NCER Year: 2014
Principal Investigator: Cook, Thomas Awardee: Northwestern University
Program: Methods Training for Education Research      [Program Details]
Award Period: 3 years (9/1/14 8/30/17) Award Amount: $955,941
Goal: Training Award Number: R305B140029
Description:

There is a continuing and pressing need for valid causal research to support education decision-making. At the same time, it is often difficult, and sometimes impossible to conduct a randomized experiment to address causal questions in education. The purpose of this series of annual workshops is to train education researchers in the design and analysis of quasi-experimental studies. Specifically, these workshops will provide training in four specific areas of quasi-experimental design and analysis: regression discontinuity, interrupted time series, nonequivalent control group design, and instrumental variables. Using an approach that expands and improves upon a previous IES training program in quasi-experimental designs (A Three Year Proposal to conduct Two Annual Workshops on Better Quasi-Experimental Design and Analysis in Education, R305U100001), the workshops will address some of the gaps and needed research in the field.

Each year for 3 years, the program will hold a 2-week workshop on quasi-experimental Methods in education research, with 30 people per workshop. The crux of the workshop is a sequence of four 2-day units on the four methods covered by the training. Each unit will include a theoretical session that introduces the basic design and analysis of the quasi-experimental design under consideration, followed by a demonstration of conducting the analyses using real data, and then an advanced topics session. Each unit also includes hands-on analyses by participants of data generated using the research design. All students who complete the training program should be able to use cutting edge methods in these four quasi-experimental designs and be able to conduct the most critical analytic tasks in some subset of these four quasi-experimental designs.


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