[go: up one dir, main page]

Si et al., 2004 - Google Patents

Ability estimation under different item parameterization and scoring models

Si et al., 2004

Document ID
81589942698018021
Author
Si C
Schumacker R
Publication year
Publication venue
International Journal of Testing

External Links

Snippet

Testing is essential in education and other social science fields because many assessments, decisions, and policies are made according to the results of testing. The purpose of testing is to estimate a person's ability, that is, latent trait or construct. In a test …
Continue reading at www.tandfonline.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/36—Computer-assisted acquisition of medical data, e.g. computerised clinical trials or questionnaires
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/708—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for data visualisation, e.g. molecular structure representations, graphics generation, display of maps or networks or other visual representations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00—Teaching not covered by other main groups of this subclass
    • G09B19/02—Counting; Calculating
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes

Similar Documents

Publication Publication Date Title
Ma et al. A sequential cognitive diagnosis model for polytomous responses
Wainer et al. Testlet response theory: An analog for the 3PL model useful in testlet-based adaptive testing
Browne Applying MCMC methods to multi-level models
Kelley et al. The MBESS r package
Yu Objective measurement: How Rasch modeling can simplify and enhance your assessment
Si et al. Ability estimation under different item parameterization and scoring models
Ferrando Likert scaling using continuous, censored, and graded response models: Effects on criterion-related validity
Chong et al. Applying the Rasch Rating Scale Model (RSM) to investigate the rating scales function in survey research instrument
Bao A diagnostic classification model for polytomous attributes
Sinharay et al. Assessment of fit of item response theory models: A critical review of the status quo and some future directions
Effatpanah et al. Kernel Smoothing Item Response Theory in R: A Didactic.
Bocell The impact of unmodeled error covariance on measurement models in structural equation modeling
Cox et al. The relation between theory and application in statistics
Shojima Test Data Engineering
von Davier et al. Reporting test outcomes using models for cognitive diagnosis
Ozaki et al. Cognitive diagnosis models for estimation of misconceptions analyzing multiple-choice data
Lao Estimation of diagnostic classification models without constraints: Issues with class label switching
van der Palm et al. A Flexible Latent Class Approach to Estimating Test‐Score Reliability
Slocum Assessing unidimensionality of psychological scales: Using individual and integrative criteria from factor analysis
Revuelta The generalized logit-linear item response model for binary-designed items
Toland Determining the accuracy of item parameter standard error of estimates in BILOG-MG 3
Bibby Plausible values: How many for plausible results
Minchen Continuous response in cognitive diagnosis models: response time modeling, computerized adaptive testing, and q-matrix validation
Klugkist et al. Bayesian estimation for inequality constrained analysis of variance
Glas Testing fit to IRT models for polytomously scored items