Confidence Envelopes for Item Response Theory

1990 ◽  
Vol 15 (2) ◽  
pp. 113-128 ◽  
Author(s):  
David Thissen ◽  
Howard Wainer
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Confidence Region ◽  
Logistic Models ◽  
Response Theory ◽  
Response Models ◽  
Item Response Models ◽  
The One

Confidence envelopes for the one-, two-, and three-parameter logistic item response models are illustrated. In addition, we describe m-line plots, which show the genesis of the envelope as well as the density of lines in the confidence region. These too are illustrated for the one-, two-, and three- parameter logistic models.

scholarly journals Improving Measurement Precision in Experimental Psychopathology Using Item Response Theory

2019 ◽  
Vol 80 (4) ◽  
pp. 695-725
Author(s):  
Leah M. Feuerstahler ◽  
Niels Waller ◽  
Angus MacDonald
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Computerized Adaptive Testing ◽  
Cognitive Task ◽  
Working Memory Capacity ◽  
Response Theory ◽  
Response Models ◽  
Item Response Models ◽  
Experimental Psychopathology ◽  
Assessment Tasks

Although item response models have grown in popularity in many areas of educational and psychological assessment, there are relatively few applications of these models in experimental psychopathology. In this article, we explore the use of item response models in the context of a computerized cognitive task designed to assess visual working memory capacity in people with psychosis as well as healthy adults. We begin our discussion by describing how item response theory can be used to evaluate and improve unidimensional cognitive assessment tasks in various examinee populations. We then suggest how computerized adaptive testing can be used to improve the efficiency of cognitive task administration. Finally, we explore how these ideas might be extended to multidimensional item response models that better represent the complex response processes underlying task performance in psychopathological populations.

scholarly journals Measuring Religious Experience: An Item Response Theory Analysis of Religious Experiences

2020 ◽  
Author(s):  
Joe Chelladurai
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Religious Experience ◽  
Logistic Models ◽  
Religion And Spirituality ◽  
Religious Experiences ◽  
Response Theory ◽  
Theory Analysis ◽  
Item Response Theory Analysis ◽  
Dichotomous Outcomes

Apart from its wide usage in educational testing and scale development, Item Response Theory analysis has not been used as much in the study of religion and spirituality. Taking advantage of the psychometric abilities of IRT, in this paper, I examine a measure of religious experiences. Particularly, I employ the Rasch model along with two parametric and three parametric logistic models for dichotomous outcomes. In general, findings from the analysis suggest low discriminatory and low difficulty parameters on the items except for one item which measured change as a result of religious experience.

Adjusting the Adjusted χ2/df Ratio Statistic for Dichotomous Item Response Theory Analyses

2011 ◽  
Vol 72 (3) ◽  
pp. 510-528 ◽  
Author(s):  
Louis Tay ◽  
Fritz Drasgow
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Logistic Models ◽  
Parametric Bootstrap ◽  
Theory Model ◽  
Item Response Theory Model ◽  
Type I ◽  
Response Theory ◽  
New Approach ◽  
The Mean

Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted χ2/ df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted χ2/ df values greater than 3 using a cross-validation data set indicate substantial misfit. The authors used simulations to examine this critical value across different test lengths (15, 30, 45) and sample sizes (500, 1,000, 1,500, 5,000). The one-, two- and three-parameter logistic models were fitted to data simulated from different logistic models, including unidimensional and multidimensional models. In general, a fixed cutoff value was insufficient to ascertain item response theory model–data fit. Consequently, the authors propose the use of the parametric bootstrap to investigate misfit and evaluated its performance. This new approach produced appropriate Type I error rates and had substantial power to detect misfit across simulated conditions. In a third study, the authors applied the parametric bootstrap approach to LSAT data to determine which dichomotous item response theory model produced the best fit. Future applications of the mean adjusted χ2/ df statistic are discussed.

scholarly journals Mokken Scale Analysis: Between the Guttman Scale and Parametric Item Response Theory

2003 ◽  
Vol 11 (2) ◽  
pp. 139-163 ◽  
Author(s):  
Wijbrandt H. van Schuur
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Classical Test Theory ◽  
Test Theory ◽  
Scale Analysis ◽  
Guttman Scale ◽  
Response Theory ◽  
Mokken Scale Analysis ◽  
Irt Models ◽  
The One

This article introduces a model of ordinal unidimensional measurement known as Mokken scale analysis. Mokken scaling is based on principles of Item Response Theory (IRT) that originated in the Guttman scale. I compare the Mokken model with both Classical Test Theory (reliability or factor analysis) and parametric IRT models (especially with the one-parameter logistic model known as the Rasch model). Two nonparametric probabilistic versions of the Mokken model are described: the model of Monotone Homogeneity and the model of Double Monotonicity. I give procedures for dealing with both dichotomous and polytomous data, along with two scale analyses of data from the World Values Study that demonstrate the usefulness of the Mokken model.

Rationalizing Delinquency: Understanding the Person-situation Interaction through Item Response Theory

2018 ◽  
Vol 56 (1) ◽  
pp. 3-41 ◽  
Author(s):  
Kyle J. Thomas
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Public High School ◽  
Response Theory ◽  
Response Models ◽  
Youth Survey ◽  
Irt Models ◽  
Situational Characteristics ◽  
Graded Response ◽  
The Individual

Objectives: I argue that a person-situation complex of delinquent rationalizations can be conceptualized by relating rationalizations to item response theory (IRT), where approval of delinquency is predominately a function of the individual willingness to rationalize ( θ j) and situational difficulty of applying a rationalization ( bi). This framework offers testable predictions and addresses extant criticisms. Method: Adolescents from a public high school ( N = 223) and subjects from the National Youth Survey ( N = 1,436) were asked their degree of approval for delinquency under various circumstances. Graded response models assessed the joint effects of individual and situational characteristics on approval of delinquency. I test whether differences in self-reported offending (SRO) and willingness to offend (WTO) are consistent with predictions derived from IRT models. Results: Approval of delinquency is a joint function of individual and situational characteristics. Some situations are so “easy” to rationalize that most everyone is predicted to approve of delinquency, and others are so “difficult” that only those very high in θ are predicted to express approval. SRO and WTO differences between individuals and situations are consistent with the IRT predictions. Conclusion: The findings demonstrate the utility of IRT for understanding delinquent rationalizations. The implications of the findings for theory and person-situation explanations are discussed.

How Do Psychologists Learn Item Response Theory?

2001 ◽  
Vol 46 (6) ◽  
pp. 629-632
Author(s):  
Robert J. Mislevy
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Response Theory
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