NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 8 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng – Measurement: Interdisciplinary Research and Perspectives, 2018
Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Identification
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Warner-Griffin, Catharine; Liu, Huili; Tadler, Chrystine; Herget, Debbie; Dalton, Ben – National Center for Education Statistics, 2017
The Progress in International Reading Literacy Study (PIRLS) is an international assessment of student performance in reading literacy at the fourth grade. PIRLS measures students in the fourth year of formal schooling because this is typically when students' learning transitions from a focus on "learning to read" to a focus on…
Descriptors: Foreign Countries, Achievement Tests, Grade 4, International Assessment
Peer reviewed Peer reviewed
Bradlow, Eric T. – Journal of Educational and Behavioral Statistics, 1996
The three-parameter logistic (3-PL) model is described and a derivation of the 3-PL observed information function is presented for a single binary response from one examinee with known item parameters. Formulas are presented for the probability of negative information and for the expected information (always nonnegative). (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
Zwick, Rebecca – 1995
This paper describes a study, now in progress, of new methods for representing the sampling variability of Mantel-Haenszel differential item functioning (DIF) results, based on the system for categorizing the severity of DIF that is now in place at the Educational Testing Service. The methods, which involve a Bayesian elaboration of procedures…
Descriptors: Adaptive Testing, Bayesian Statistics, Classification, Computer Assisted Testing
Allen, Nancy L.; Donoghue, John R. – 1995
This Monte Carlo study examined the effect of complex sampling of items on the measurement of differential item functioning (DIF) using the Mantel-Haenszel procedure. Data were generated using a three-parameter logistic item response theory model according to the balanced incomplete block (BIB) design used in the National Assessment of Educational…
Descriptors: Computer Assisted Testing, Difficulty Level, Elementary Secondary Education, Identification
Thompson, Bruce; Melancon, Janet G. – 1990
Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…
Descriptors: Comparative Analysis, Computer Assisted Testing, Correlation, Effect Size
Peer reviewed Peer reviewed
Rock, Donald A.; Nelson, Jennifer – Journal of Educational Statistics, 1992
Several developments growing out of the National Assessment of Educational Progress (NAEP) are reviewed, with a discussion of their extension and application to other projects. These developments include: (1) complex matrix item sampling designs; (2) performance-based items in large-scale assessments; (3) vertical scaling; and (4) innovative…
Descriptors: Computer Assisted Testing, Educational Assessment, Elementary Secondary Education, Evaluation Methods
van der Linden, Wim J. – 1988
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with multiple item parameters. The models are able to cope…
Descriptors: Ability Identification, Computer Assisted Testing, Elementary Education, Elementary School Students