Screening for aberrant school performances in high-stakes assessments using in influential analysis
by Andrés Christiansen; Rianne Janssen; Cristian Luis Bayes
International Journal of Quantitative Research in Education (IJQRE), Vol. 5, No. 2, 2020

Abstract: A method is proposed to screen for aberrant school performances in large-scale, high-stakes assessments using influential analysis under a Bayesian approach. Proportions of low and high achievers within a school were modelled via the beta inflated mean regression model (Bayes and Valdivieso, 2016) using school performances in previous years as predictors. The general measure of ϕ-divergence proposed by Peng and Dey (1995) was used to determine aberrancy. A simulation study revealed that the method could recover previously distorted school performances as aberrant. The proposed technique was applied to a Peruvian national reading assessment in grade 4th of primary education for which the government provided a school performance incentive bonus.

Online publication date: Fri, 27-Nov-2020

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