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Kenna, Ralph; Berche, Bertrand – Higher Education Management and Policy, 2012
Smaller universities may produce research which is on a par with larger, elite establishments. This is confirmed by a recently developed mathematical model, supported by data from British and French higher education research-evaluation exercises. The detailed nature of the UK system, in particular, allows quantification of the notion of critical…
Descriptors: Foreign Countries, Higher Education, Mathematical Models, Research Universities
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
Klitgaard, Robert E. – 1975
To the data analyst, outliers can present both a problem and an opportunity. Stray or outlying observations can severly distort estimates of a distribution's central tendency (like the mean) and estimates of one variable's relationship to another (like the regression coefficient). These problems are frequent and serious, and as a result,…
Descriptors: Data Analysis, Demonstration Programs, Educational Quality, Identification
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Ashenfelter, Orley – Review of Economics and Statistics, 1978
Available from: the North-Holland Publishing Company, P.O. Box 211, Amsterdam, The Netherlands. (JG)
Descriptors: Data Analysis, Educational Economics, Evaluation Methods, Federal Programs
Murray, James R.; Wiley, David E. – 1970
A basic methodological approach in developmental studies is the collection of longitudinal data. Behavioral data cen take at least two forms, qualitative (or discrete) and quantitative. Both types are fallible. Measurement errors can occur in quantitative data and measures of these are based on error variance. Qualitative or discrete data can…
Descriptors: Behavioral Sciences, Data Analysis, Evaluation Methods, Feedback
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Bryk, Anthony S.; Weisberg, Herbert I. – Journal of Educational Statistics, 1976
Focuses on the fact that an educational treatment typically involves an intervention in a growth process. By modelling this process, expected growth for various treatment groups under control conditions may be estimated. Actual growth can be compared with projected growth to estimate the value-added by the program. A simple model is developed. (RC)
Descriptors: Analysis of Covariance, Comparative Analysis, Control Groups, Data Analysis
Smith, Nick L.; Murray, Stephen L. – 1978
Path analysis, a technique related to multiple regression analysis is used for ascribing causal relationships among variables. Path analysis involves the construction of explicitly formulated causal models and makes the reasoning explicit in the form of path diagrams and structural equations. Regression analysis is then used to construct path…
Descriptors: Correlation, Critical Path Method, Data Analysis, Educational Research
Yap, Kim Onn – 1979
The accuracy with which regression models estimate treatment effects is dependent upon a number of conditions. The stability of the regression line (a function of sample size and correlation between pretest and posttest) is said to be the most important of these conditions. The utility of regression models is proportional to the size of the…
Descriptors: Correlation, Data Analysis, Educational Testing, Evaluation Methods
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