Results 251 to 260 of about 690,612 (290)

A Model Fit Statistic for Generalized Partial Credit Model

Educational and Psychological Measurement, 2009
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S.
Liang, T, Wells, CS
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The Partial Credit Model and Generalized Partial Credit Model as Constrained Nominal Response Models, With Applications in Mplus

Structural Equation Modeling: A Multidisciplinary Journal, 2015
The purpose of this article is to demonstrate constraining the nominal response model in Mplus software to calibrate data under the partial credit model (PCM) and generalized partial credit model (GPCM). Currently, many researchers are uncertain if the PCM and GPCM can be estimated within Mplus.
Anne Corinne Huggins-Manley, James Algina   +1 more
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The Hills…with the Partial Credit Model

2020
In Rasch Analysis in the Human Sciences we discussed at length the use of what we named “The Hills” (Chap. 9 How Well Does That Rating Scale Work? How Do You Know, Too?). The Hills provide a technique by which analysts can evaluate how each rating scale step is helping to measure each respondent.
William J. Boone, John R. Staver
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A Generalized Partial Credit Model

1997
A generalized partial credit model (GPCM) was formulated by Muraki (1992) based on Masters’ (1982, this volume) partial credit model (PCM) by relaxing the assumption of uniform discriminating power of test items. However, the difference between these models is not only the parameterization of item characteristics but also the basic assumption about the
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Fitting and Testing Conditional Multinormal Partial Credit Models

Psychometrika, 2012
A multinormal partial credit model for factor analysis of polytomously scored items with ordered response categories is derived using an extension of the Dutch Identity (Holland in Psychometrika 55:5–18, 1990). In the model, latent variables are assumed to have a multivariate normal distribution conditional on unweighted sums of item scores, which are ...
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Parameter estimation for finite mixtures of partial credit models

Proceedings of the 2007 international conference on Computer systems and technologies - CompSysTech '07, 2007
We consider a test of finite length and assume that each item has m ≥ 2 graded response categories which satisfy the Partial Credit Model (PCM) from the Item Response Theory [1--4] and also that there exist K population classes which differ in the parameter values.
Dimiter Tsvetkov, Lyubomir Hristov
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Partial Credit Model

2022
Stefanie A. Wind, Cheng Hua
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An EPQ model under partial trade credit financing with credit sensitive demand

2010 IEEE International Conference on Industrial Engineering and Engineering Management, 2010
Trade credit is an increasingly important payment behavior in real business transactions. In practice, the supplier allows a certain fixed credit period to settle the account for stimulating retailer's demand. From the retailer's viewpoint, during the credit period before payment must be made, he/she can sell the items and continue to accumulate ...
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Applying the Partial Credit Model to Educational Diagnosis

Applied Measurement in Education, 1988
Diagnosis has been a popular aim of educational testing for many years, but it has continued with limited success. The diagnostic interpretation of test data is most effective when students' responses are referred to a frame of reference describing the types and level of understanding that students have of specific concepts. This article shows how such
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An Option-Based Partial Credit Item Response Model

2015
Multiple-choice (MC) tests have been criticized for allowing guessing and the failure to credit partial knowledge, and alternative scoring methods and response formats (Ben-Simon et al., Appl Psychol Meas 21:65–88, 1997) have been proposed to address this problem. Modern test theory addresses these issues by using binary item response models (e.g., 3PL)
Yuanchao Bo, Charles Lewis, David V. Budescu   +2 more
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