Author
Stephen W. Raudenbush
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ResourceIt’s No Longer All about the Mean: Using Multi-site Trials to Learn About and From Impact Variation
Raudenbush and Bloom outline key features of an ambitious project project that will bring together prominent university-based methodologists and the three research firms (MDRC, Mathematica Policy Research, and Abt Associates, Inc.) that have conducted the most large multi-site trials in education, youth development, and related fields. This paper describes the project's statistical foundation, and identifies its anticipated benefits. The project is organized in two parts: 1) developing and applying methods for learning about impact variation and 2) developing and applying methods for learning from impact variation.
Research MethodsAnalyzing Multilevel Trials -
ResourceConfidence Bounds and Power for the Reliability of Observational Measures on the Quality of a Social Setting
"Social scientists are frequently interested in assessing the qualities of social settings such as classrooms, schools, neighborhoods, or day care centers. The most common procedure requires observers to rate social interactions within these settings on multiple items and then to combine the item responses to obtain a summary measure of setting quality. A key aspect of the quality of such a summary measure is its reliability. In this paper we derive a confidence interval for reliability, a test for the hypothesis that the reliability meets a minimum standard, and the power of this test against alternative hypotheses. Next, we consider the problem of using data from a preliminary field study of the measurement procedure to inform the design of a later study that will test substantive hypotheses about the correlates of setting quality."
Research Methods -
ResourceStudying the Reliability of Group-Level Measures with Implications for Statistical Power: A Six-Step Paradigm
Many youth development programs aim to improve youth outcomes by raising the quality of social interactions occurring in groups such as classrooms, athletic teams, therapy groups, after-school programs, or recreation centers. As a result, evaluators are increasingly interested in determining whether such programs significantly improve “group quality.” This paper consider methods for studying the reliability of measures of group quality, with implications for the design of evaluation studies, and illustrates these methods using a large-scale data set on classroom observations.
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