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Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – Educational Evaluation and Policy Analysis, 2012
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Educational Research, Educational Researchers, Research Methodology, Multivariate Analysis
Kissel, Mary Ann; Yeager, John L. – 1971
Several sampling procedures for collecting observational data on student activities were studied in an effort to determine their relative efficiency. The setting was a fifth grade Individually Prescribed Instruction (IPI) mathematics class of thirty-three pupils. A criterion measure was obtained by cumulating the measurements obtained on the…
Descriptors: Class Activities, Classroom Observation Techniques, Comparative Analysis, Data Collection
Bianchini, John C.; Loret, Peter G. – 1974
The Anchor Test Study provides a method for translating a pupil's score on any one of eight widely used standardized reading tests for Grades 4, 5, and 6 to a corresponding score on any of the other seven tests, as well as furnishing new nationally representative norms for each of the eight tests. In addition, the Study presents new estimates of…
Descriptors: Administration, Comparative Analysis, Correlation, Data Collection
Bianchini, John C.; Loret, Peter G. – 1974
The Anchor Test Study provides a method for translating a pupil's score on any one of eight widely used standardized reading tests for Grades 4, 5, and 6 to a corresponding score of any of the other seven tests, as well as furnishing new nationally representative norms for each of the eight tests. In addition, the Study presents new estimates of…
Descriptors: Administration, Comparative Analysis, Correlation, Data Collection
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Marascuilo, Leonard A. – Journal of Experimental Education, 1979
The utility of the biomedical model of adjusted statistics is demonstrated. The model is recommended for use by educational researchers to randomize subjects for a more accurate estimate of school programs' success or failure when compared across classrooms or other units. (Author/MH)
Descriptors: Academic Achievement, Analysis of Variance, Comparative Analysis, Criterion Referenced Tests