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| Burstein, Leigh | 1 |
| Conklin, Jonathan E. | 1 |
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| Magidson, Jay | 1 |
| Tallmadge, G. Kasten | 1 |
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Conklin, Jonathan E.; Burstein, Leigh – 1979
Educational outcomes are affected by student level, classroom level, and school level characteristics. The fact that educational data are multilevel in nature poses serious analysis questions. Though strong arguments can be made for focusing on a single level of analysis, such studies have several basic limitations: the choice of analytic level…
Descriptors: Analysis of Covariance, Correlation, Data Analysis, Mathematical Models
Magidson, Jay – 1977
In evaluation research studies, it often occurs that several program participants (experimentals) drop out of the program prior to completion. Since noncompleters generally differ substantially from completers in many respects, a control group which originally was representative of the participant group will most likely not be representative of…
Descriptors: Attrition (Research Studies), Career Education, Control Groups, Discriminant Analysis
Linn, Robert L. – 1978
The three RMC models endorsed by the U.S. Office of Education for the evaluation of Elementary and Secondary Education Act Title I programs are based on narrowly conceived approaches to evaluation--the measurement of cognitive achievement gains. Each model requires the comparison of observed student performance with an estimate of what level of…
Descriptors: Academic Achievement, Achievement Gains, Compensatory Education, Control Groups
Horst, Donald P.; Tallmadge, G. Kasten – 1976
The orientation of this report is that of identifying educational projects which can be considered clearly exemplary. The largest section consists of a 22-step procedure for validating the effectiveness of educational projects using existing evaluation data. It is not intended as a guide for conducting evaluations but rather for interpreting data…
Descriptors: Academic Achievement, Achievement Gains, Compensatory Education, Control Groups


