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Bergner, Yoav; von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2019
This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…
Descriptors: National Competency Tests, Data Collection, Data Analysis, Cognitive Processes
Zhang, Jinming – Journal of Educational and Behavioral Statistics, 2012
The impact of uncertainty about item parameters on test information functions is investigated. The information function of a test is one of the most important tools in item response theory (IRT). Inaccuracy in the estimation of test information can have substantial consequences on data analyses based on IRT. In this article, the major part (called…
Descriptors: Item Response Theory, Tests, Accuracy, Data Analysis
Peer reviewedWainer, Howard – Journal of Educational and Behavioral Statistics, 1997
Four guidelines that make tables more effective data displays are presented. The need for these guidelines and their application are illustrated with data from the National Assessment of Educational Progress (NAEP). A theoretical structure is presented to help develop test items to assess students' proficiency in extracting information from…
Descriptors: Comprehension, Data Interpretation, Elementary Secondary Education, Information Dissemination
Peer reviewedThomas, Neal; Gan, Nianci – Journal of Educational and Behavioral Statistics, 1997
Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…
Descriptors: Data Analysis, Item Response Theory, Matrices, Maximum Likelihood Statistics

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