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• W2127249662 abstract "To what extent does individual student change (growth) over the academic year statistically explain why students differ in end-of-year performance after accounting for performance on interim assessments? The four growth estimates examined in this report (simple difference, average difference, ordinary least squares, and empirical Bayes) all contributed significantly to predicting performance on the end-of-year criterion-referenced reading test when performance on the initial (fall) interim assessment was used as a covariate. The simple difference growth estimate was the best predictor when controlling for mid-year (winter) status, and all but the simple difference estimate contributed significantly when controlling for final (spring) status. Quantile regression suggested that the relations between growth and the outcome were conditional on the outcome, implying that traditional linear regression analyses could mask the predictive relations." @default.
• W2127249662 created "2016-06-24" @default.
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• W2127249662 date "2014-01-01" @default.
• W2127249662 modified "2023-09-27" @default.
• W2127249662 title "Testing the Importance of Individual Growth Curves in Predicting Performance on a High-Stakes Reading Comprehension Test in Florida. Summary. REL 2014-006." @default.
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• W2127249662 hasPublicationYear "2014" @default.
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