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Rhoads, Christopher – Society for Research on Educational Effectiveness, 2016
Current practice for conducting power analyses in hierarchical trials using survey based ICC and effect size estimates may be misestimating power because ICCs are not being adjusted to account for treatment effect heterogeneity. Results presented in Table 1 show that the necessary adjustments can be quite large or quite small. Furthermore, power…
Descriptors: Statistical Analysis, Correlation, Effect Size, Surveys
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Kelcey, Ben – Society for Research on Educational Effectiveness, 2015
Like studies focused on the detection of a main or total effect, a principal consideration in the design of studies examining mediation is the power with which mediation effects can be detected if they exist (e.g., Raudenbush, 1997). However, unlike studies concerning the detection of main effects, literature has not established power formulas for…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Effect Size, Mathematical Formulas
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Hedberg, E. C.; Hedges, L. V.; Kuyper, A. M. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are generally considered to provide the strongest basis for causal inferences about cause and effect. Consequently randomized field trials have been increasingly used to evaluate the effects of education interventions, products, and services. Populations of interest in education are often hierarchically structured (such as…
Descriptors: Randomized Controlled Trials, Hierarchical Linear Modeling, Correlation, Computation
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Westine, Carl D. – Society for Research on Educational Effectiveness, 2015
A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…
Descriptors: Correlation, Randomized Controlled Trials, Science Achievement, Cluster Grouping
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May, Henry; Sirinides, Philip; Gray, Abby; Davila, Heather Goldsworthy; Sam, Cecile; Blalock, Toscha; Blackman, Horatio; Anderson-Clark, Helen; Schiera, Andrew J. – Society for Research on Educational Effectiveness, 2015
As part of the 2010 economic stimulus, a $55 million "Investing in Innovation" (i3) grant from the US Department of Education was awarded to scale up Reading Recovery across the nation. This paper presents the final round of results from the large-scale, mixed methods randomized evaluation of the implementation and impacts of Reading…
Descriptors: Reading Programs, Program Evaluation, Reading Achievement, Mixed Methods Research
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Polanin, Joshua R.; Wilson, Sandra Jo – Society for Research on Educational Effectiveness, 2014
The purpose of this project is to demonstrate the practical methods developed to utilize a dataset consisting of both multivariate and multilevel effect size data. The context for this project is a large-scale meta-analytic review of the predictors of academic achievement. This project is guided by three primary research questions: (1) How do we…
Descriptors: Meta Analysis, Correlation, Case Studies, Parent Participation
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Westine, Carl; Spybrook, Jessaca – Society for Research on Educational Effectiveness, 2013
The capacity of the field to conduct power analyses for group randomized trials (GRTs) of educational interventions has improved over the past decade (Authors, 2009). However, a power analysis depends on estimates of design parameters. Hence it is critical to build the empirical base of design parameters for GRTs across a variety of outcomes and…
Descriptors: Randomized Controlled Trials, Research Design, Correlation, Program Effectiveness
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Faria, Ann-Marie; Greenberg, Ariela; Meakin, John; Bichay, Krystal; Heppen, Jessica – Society for Research on Educational Effectiveness, 2014
Educators have long used test scores to make educational decisions, but only within the last decade has the availability of data been systematic (Abelman, Elmore, Even, Kenyon, & Marshall, 1999). In recent years, interest has spiked in data-driven decision making in education (Marsh, Pane, & Hamilton, 2006). With technological advances and…
Descriptors: Data Analysis, Academic Achievement, Urban Schools, Correlation