An Item Response Model for Multidimensional Analysis of Multiple-Choice Data

1996 ◽  
Vol 23 (2) ◽  
pp. 153-167 ◽  
Author(s):  
Yoshio Takane
Keyword(s):  
Item Response ◽  
Multiple Choice ◽  
Multidimensional Analysis ◽  
Response Model ◽  
Item Response Model ◽  
Choice Data

A Mixture Item Response Model for Multiple-Choice Data

2001 ◽  
Vol 26 (4) ◽  
pp. 381-409 ◽  
Author(s):  
Daniel M. Bolt ◽  
Allan S. Cohen ◽  
James A. Wollack
Keyword(s):  
Item Response ◽  
Multiple Choice ◽  
Test Construction ◽  
Item Parameter ◽  
Monte Carlo Algorithm ◽  
Choice Test ◽  
Model Parameters ◽  
Response Model ◽  
Item Response Model ◽  
Choice Data

A mixture item response model is proposed for investigating individual differences in the selection of response categories in multiple-choice items. The model accounts for local dependence among response categories by assuming that examinees belong to discrete latent classes that have different propensities towards those responses. Varying response category propensities are captured by allowing the category intercept parameters in a nominal response model ( Bock, 1972 ) to assume different values across classes. A Markov Chain Monte Carlo algorithm for the estimation of model parameters and classification of examinees is described. A real-data example illustrates how the model can be used to distinguish examinees that are disproportionately attracted to different types of distractors in a test of English usage. A simulation study evaluates item parameter recovery and classification accuracy in a hypothetical multiple-choice test designed to be diagnostic. Implications for test construction and the use of multiple-choice tests to perform cognitive diagnoses of item response patterns are discussed.

scholarly journals Quantifying Liver Stagnation Spleen Deficiency Pattern for Diarrhea Predominate Irritable Bowel Syndromes Using Multidimensional Analysis Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongyu Huang ◽  
Zhengkun Hou ◽  
Xianhua Liu ◽  
Fengbin Liu ◽  
Yuefeng Wu
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Item Response ◽  
Multidimensional Analysis ◽  
Rational Approach ◽  
Response Model ◽  
Item Response Model ◽  
Multidimensional Item Response ◽  
Spleen Deficiency ◽  
Analysis Methods

Objective. This study aims to offer a new approach for quantifying severity of traditional Chinese medicine pattern with multidimensional analysis methods. Methods. A scale and theoretical models were constructed based on the definition of liver stagnation spleen deficiency pattern. Clinical data of 344 IBS-D patients from a cross-sectional study was used for feature validation of the model. Confirmatory factor analysis was used for evaluating the models. Also, multidimensional item response model was used for assessing multidimensional psychometric properties of the scale. Results. Detecting two latent traits, the Cronbach’s alpha of the 9-item scale was 0.745. Multidimensional model was evaluated with significant goodness of fit indices while the unidimensional model was rejected. The multidimensional item response model showed all the items had adequate discrimination. Parameters presented adequate explanation regarding mental syndromes having high factor loading on the liver stagnation factor and abdominal discomfort syndromes highly related to the spleen deficiency factor. Test information function showed that scale demonstrated the highest discrimination power among patients with moderate to high level of severity. Conclusions. The application of the multidimensional analysis methods on the basis of theoretical model construction provides a useful and rational approach for quantifying the severity of traditional Chinese medicine patterns.

scholarly journals Random Item Response Model Approaches to Evaluating Item Format Effects

2018 ◽  
Vol 8 (3) ◽  
pp. 98
Author(s):  
Yongsang Lee ◽  
Inyong Park
Keyword(s):  
Item Response ◽  
Multiple Choice ◽  
Test Model ◽  
Science Assessment ◽  
Response Model ◽  
Item Response Model ◽  
Item Format ◽  
Data Set ◽  
Format Effects ◽  
Pisa 2006

The PISA 2006 science assessment is composed of open response, multiple-choice, and constructed multiple choice items. The current study introduced the random item response models to investigate the item format effects on item difficulties, and these models include the linear logistic test model with raThe PISA 2006 science assessment is composed of open response, multiple-choice, and constructed multiple choice items. The current study introduced the random item response models to investigate the item format effects on item difficulties, and these models include the linear logistic test model with random item effects (i.e., the LLTM-R) and the hierarchical item response model (i.e., the hierarchical IRM). In this study these models were applied to the PISA 2006 science data set to explore the relationship between items' format and their difficulties. The empirical analysis results in the PISA 2006 science assessment first find that the LLTM-R and the hierachical IRM provides equivalent item difficulty estimates compared with those from the Rasch model and the LLTM, and also clearly show that the item difficulties are substantially affected by item formats. This result implies that item difficulties may be different to each other depending on the item format although they deal with the same content.ndom item effects (i.e., the LLTM-R) and the hierarchical item response model (i.e., the hierarchical IRM). In this study these models were applied to the PISA 2006 science data set to explore the relationship between items' format and their difficulties. The empirical analysis results in the PISA 2006 science assessment first find that the LLTM-R and the hierachical IRM provides equivalent item difficulty estimates compared with those from the Rasch model and the LLTM, and also clearly show that the item difficulties are substantially affected by item formats. This result implies that item difficulties may be different to each other depending on the item format although they deal with the same content.

scholarly journals Forced-Choice Assessment of Work-Related Maladaptive Personality Traits: Preliminary Evidence From an Application of Thurstonian Item Response Modeling

Assessment ◽  
2016 ◽  
Vol 25 (4) ◽  
pp. 513-526 ◽  
Author(s):  
Nigel Guenole ◽  
Anna A. Brown ◽  
Andrew J. Cooper
Keyword(s):  
Item Response ◽  
Goodness Of Fit ◽  
Stimulus Item ◽  
Forced Choice ◽  
Single Stimulus ◽  
Response Model ◽  
Item Response Model ◽  
Choice Data ◽  
Item Response Modeling ◽  
Response Modeling

This article describes an investigation of whether Thurstonian item response modeling is a viable method for assessment of maladaptive traits. Forced-choice responses from 420 working adults to a broad-range personality inventory assessing six maladaptive traits were considered. The Thurstonian item response model’s fit to the forced-choice data was adequate, while the fit of a counterpart item response model to responses to the same items but arranged in a single-stimulus design was poor. Monotrait heteromethod correlations indicated corresponding traits in the two formats overlapped substantially, although they did not measure equivalent constructs. A better goodness of fit and higher factor loadings for the Thurstonian item response model, coupled with a clearer conceptual alignment to the theoretical trait definitions, suggested that the single-stimulus item responses were influenced by biases that the independent clusters measurement model did not account for. Researchers may wish to consider forced-choice designs and appropriate item response modeling techniques such as Thurstonian item response modeling for personality questionnaire applications in industrial psychology, especially when assessing maladaptive traits. We recommend further investigation of this approach in actual selection situations and with different assessment instruments.

scholarly journals Extensions of the skew-normal ogive item response model

2014 ◽  
Vol 28 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Jorge Luis Bazán ◽  
Márcia D. Branco ◽  
Heleno Bolfarine
Keyword(s):  
Item Response ◽  
Response Model ◽  
Item Response Model ◽  
Skew Normal

Are Teachers' Unions Really to Blame? Collective Bargaining Agreements and Their Relationships with District Resource Allocation and Student Performance in California

2011 ◽  
Vol 6 (3) ◽  
pp. 354-398 ◽  
Author(s):  
Katharine O. Strunk
Keyword(s):  
Resource Allocation ◽  
Collective Bargaining ◽  
Student Performance ◽  
Item Response ◽  
Response Model ◽  
Item Response Model ◽  
Teachers Unions ◽  
Achievement Growth ◽  
Unique Measure ◽  
Level Student

Increased spending and decreased student performance have been attributed in part to teachers' unions and to the collective bargaining agreements (CBAs) they negotiate with school boards. However, only recently have researchers begun to examine impacts of specific aspects of CBAs on student and district outcomes. This article uses a unique measure of contract restrictiveness generated through the use of a partial independence item response model to examine the relationships between CBA strength and district spending on multiple areas and district-level student performance in California. I find that districts with more restrictive contracts have higher spending overall, but that this spending appears not to be driven by greater compensation for teachers but by greater expenditures on administrators' compensation and instruction-related spending. Although districts with stronger CBAs spend more overall and on these categories, they spend less on books and supplies and on school board–related expenditures. In addition, I find that contract restrictiveness is associated with lower average student performance, although not with decreased achievement growth.

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