Results 281 to 290 of about 2,443,182 (340)

Attention Allocation for Dysphoric Information in Adults with Depression Symptoms Using Eye-tracking and Mouse-tracking. [PDF]

PLoS One
McNamara ME, Shumake J, Beevers CG.
europepmc   +1 more source

The Impact of Diet Quality on COVID-19 Severity and Outcomes-A Scoping Review. [PDF]

Curr Nutr Rep
Tassakos A, Kloppman A, Louie JCY.
europepmc   +1 more source

The Effect of Modeling Missing Data With IRTree Approach on Parameter Estimates Under Different Simulation Conditions. [PDF]

Educ Psychol Meas
Soğuksu YB, Demir E.
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The Chinese Version of the DigiHealthCom (Digital Health Competence) Instrument for Assessing Digital Health Competence of Health Care Professionals: Translation, Adaptation, and Validation Study.

JMIR Hum Factors
Gao L, Chen M, Wei J, Wang J, Liao X.
europepmc   +1 more source

CONSORT 2025 explanation and elaboration: updated guideline for reporting randomised trials.

BMJ
Hopewell S, Chan AW, Collins GS, Hróbjartsson A, Moher D, Schulz KF, Tunn R, Aggarwal R, Berkwits M, Berlin JA, Bhandari N, Butcher NJ, Campbell MK, Chidebe RCW, Elbourne D, Farmer A, Fergusson DA, Golub RM, Goodman SN, Hoffmann TC, Ioannidis JPA, Kahan BC, Knowles RL, Lamb SE, Lewis S, Loder E, Offringa M, Ravaud P, Richards DP, Rockhold FW, Schriger DL, Siegfried NL, Staniszewska S, Taylor RS, Thabane L, Torgerson D, Vohra S, White IR, Boutron I.   +38 more
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Investigating Item Bias in a CS1 Exam with Differential Item Functioning [PDF]

Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, 2021
Reliable and valid exams are a crucial part of both sound research design and trustworthy assessment of student knowledge. Assessing and addressing item bias is a crucial step in building a validity argument for any assessment instrument. Despite calls for valid assessment tools in CS, item bias is rarely investigated.
Matt J. Davidson, Amy J. Ko, Brett Wortzman, Min Li   +3 more
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AN ITERATIVE ITEM BIAS DETECTION METHOD

Journal of Educational Measurement, 1984
Two strategies for assessing item bias are discussed: methods that compare (transformed) item difficulties unconditional on ability level and methods that compare the probabilities of correct response conditional on ability level. In the present study, the logit model was used to compare the probabilities of correct response to an item by members of ...
Henk Van Der Flier, Gideon J. Mellenbergh, Marina Wijn, H.J. Adèr   +3 more
openaire   +3 more sources

Item bias detection: Modern approaches

2005
A general definition of differential item functioning (DIF) is presented. The definition is specified for DIF between two groups and a test (questionnaire) that measures one latent trait. Methods for DIF detection are described for dichotomous, ordinal-polytomous, and continuous item responses under unidimensional item response theory (IRT) models.
G. Mellenbergh
openaire   +5 more sources

Detecting Item BIAS in Affective Scales

Educational and Psychological Measurement, 1987
The purpose of the study was to demonstrate the use of confirmatory factor analysis to investigate the existence of item bias in an affective scale measuring self-concept. The data were collected from three ethnic groups (Black, Hispanic, and White) in grade eight (N = 1264). The factor structure and item uniqueness were simultaneously compared across
J. Benson
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Contingency Table Models for Assessing Item Bias

Journal of Educational Statistics, 1982
Two strategies for assessing item bias are discussed: Methods based on Item x Group interaction and methods that compare the probabilities of a correct response for different groups conditional on ability level. In latent trait models, correct response probabilties are compared conditional on latent ability; in Scheuneman’s (1979) method these ...
G. Mellenbergh
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