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Linn, Robert L. – Journal of Educational Measurement, 1983
When the precise basis of selection effect on correlation and regression equations is unknown but can be modeled by selection on a variable that is highly but not perfectly related to observed scores, the selection effects can lead to the commonly observed "overprediction" results in studies of predictive bias. (Author/PN)
Descriptors: Bias, Correlation, Higher Education, Prediction

Slinde, Jeffrey A.; Linn, Robert L. – Journal of Educational Measurement, 1979
The Rasch model was used to equate reading comprehension tests of widely different difficulty for three groups of fifth grade students of widely different ability. Under these extreme circumstances, the Rasch model equating was unsatisfactory. (Author/CTM)
Descriptors: Academic Ability, Bias, Difficulty Level, Equated Scores

Linn, Robert L.; Dunbar, Stephen B. – Journal of Educational Measurement, 1992
Several issues related to the design and reporting of results from the National Assessment of Educational Progress (NAEP) are discussed in the context of current expectations for the NAEP and its origins. These issues include: (1) content coverage and format; (2) estimation procedures; and (3) reporting problems. (SLD)
Descriptors: Content Analysis, Educational Assessment, Elementary Secondary Education, Estimation (Mathematics)
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