Using place-based randm assignment and comparative interrupted time-serie analysis to evaluate the jobs-plus employment program for public housing residents
By: BLOOM, Howard S
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Contributor(s): RICCIO, James A.
Material type: 
ArticlePublisher: Thousand Oaks : SAGE, May 2005The Annals of The American Academy of Political and Social Science 599, p. 19-51Abstract: This article describes a place-based research demonstration program to promote and sustain employment aming residents of selected public housing developments in six U.S. cities. Because all eligible residents of the participating public housing developments were free to take part in the program, it was not possible to study its impacts in a classical experiment, with random assignment of individual residents to the program or a control group. Instead, the impact analysis is based on a design that selected matched groups of two or three public housing developments in each participating city and randomly assigned one ti the program and the other(s) to a control group. In addition, an eleven-year comparative interrupted time-series analysis is being used to strengthen the place-based random assignment design. Preliminary analyses of baseline data suggest that this two-pronged approach will provide credible estimates of program impacts.
This article describes a place-based research demonstration program to promote and sustain employment aming residents of selected public housing developments in six U.S. cities. Because all eligible residents of the participating public housing developments were free to take part in the program, it was not possible to study its impacts in a classical experiment, with random assignment of individual residents to the program or a control group. Instead, the impact analysis is based on a design that selected matched groups of two or three public housing developments in each participating city and randomly assigned one ti the program and the other(s) to a control group. In addition, an eleven-year comparative interrupted time-series analysis is being used to strengthen the place-based random assignment design. Preliminary analyses of baseline data suggest that this two-pronged approach will provide credible estimates of program impacts.
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