scholarly journals Joint modeling of the two-alternative multidimensional forced-choice personality measurement and its response time by a Thurstonian D-diffusion item response model

2020 ◽  
Vol 52 (3) ◽  
pp. 1091-1107
Author(s):  
Kyosuke Bunji ◽  
Kensuke Okada
Keyword(s):  
Response Time ◽  
Item Response ◽  
Joint Modeling ◽  
Forced Choice ◽  
Response Model ◽  
Personality Measurement ◽  
Item Response Model

scholarly journals The best of both worlds: a joint modeling approach for the assessment of change across repeated measurements

2010 ◽  
Vol 3 (1) ◽  
pp. 176-207 ◽  
Author(s):  
Chueh An Hsieh ◽  
Alexander Von Eye
Keyword(s):  
Item Response ◽  
Bayesian Methods ◽  
Latent Variable ◽  
Joint Modeling ◽  
Small Sample ◽  
Repeated Measurements ◽  
Latent Variable Model ◽  
Response Model ◽  
Item Response Model ◽  
Variable Model

The usefulness of Bayesian methods in estimating complex statistical models is undeniable. From a Bayesian standpoint, this paper aims to demonstrate the capacity of Bayesian methods and propose a comprehensive model combining both a measurement model (e.g., an item response model, IRM) and a structural model (e.g., a latent variable model, LVM). That is, through the incorporation of the probit link and Bayesian estimation, the item response model can be introduced naturally into a latent variable model. The utility of this IRM-LVM comprehensive framework is investigated with a real data example and promising results are obtained, in which the data drawn from part of the British Social Attitudes Panel Survey 1983-1986 reveal the attitude toward abortion of a representative sample of adults aged 18 or older living in Great Britain. The application of IRMs to responses gathered from repeated assessments allows us to take the characteristics of both item responses and measurement error into consideration in the analysis of individual developmental trajectories, and helps resolve some difficult modeling issues commonly encountered in developmental research, such as small sample sizes, multiple discretely scaled items, many repeated assessments, and attrition over time.

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.

Psychology of Computer Use: VIII. Utilizing a Nonparametric Item Response Model to Develop Unidimensional Scales: Mokscal

1989 ◽  
Vol 68 (3) ◽  
pp. 987-1000 ◽  
Author(s):  
Elisabeth Tenvergert ◽  
Johannes Kingma ◽  
Terry Taerum
Keyword(s):  
Item Response ◽  
Goodness Of Fit ◽  
Functional Form ◽  
Search Procedure ◽  
Response Model ◽  
Scale Analysis ◽  
Item Response Model ◽  
Goodness Of Fit Test ◽  
Item Coefficient ◽  
Nonparametric Item Response

MOKSCAL is a program for the Mokken (1971) scale analysis based on a nonparametric item response model that makes no assumptions about the functional form of the item trace lines. The only constraint the Mokken model puts on the trace lines is the assumption of double monotony; that is, the item trace lines must be nondecreasing and the lines are not allowed to cross. MOKSCAL provides three procedures of scaling: a search procedure, an evaluation of the whole set of items, and an extension of an existing scale. All procedures provide a coefficient of scalability for all items that meet the criteria of the Mokken model and an item coefficient of scalability of every item. A test of robustness of the found scale can be performed to analyze whether the scale is invariant across different subgroups or samples. This robustness test may serve as a goodness-of-fit test for the established scale. The program is written in FORTRAN 77 and is suitable for both mainframe and microcomputers.

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