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Tipton, Elizabeth – Journal of Educational and Behavioral Statistics, 2013
As a result of the use of random assignment to treatment, randomized experiments typically have high internal validity. However, units are very rarely randomly selected from a well-defined population of interest into an experiment; this results in low external validity. Under nonrandom sampling, this means that the estimate of the sample average…
Descriptors: Generalization, Experiments, Classification, Computation
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2013
This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…
Descriptors: Computation, Causal Models, Statistical Inference, Nonparametric Statistics
Hong, Guanglei; Raudenbush, Stephen W. – Journal of Educational and Behavioral Statistics, 2008
The authors propose a strategy for studying the effects of time-varying instructional treatments on repeatedly observed student achievement. This approach responds to three challenges: (a) The yearly reallocation of students to classrooms and teachers creates a complex structure of dependence among responses; (b) a child's learning outcome under a…
Descriptors: Elementary School Mathematics, Grade 4, Probability, Teaching Methods

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