A Pearson-Type-VII item response model for assessing person fluctuation

Ferrando, Pere J.

doi:10.1007/s11336-004-1170-0

Cited by 16 publications

(38 citation statements)

References 53 publications

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“…Strandmark and Linn (1987) presented a 2PL model for person fit (see al.so Ferrando, 2007;Reise, 20(M)). Of interest, their 2PL model is similar to the D-diffusion item response model.…”

Section: (15)mentioning

confidence: 99%

Cognitive psychology meets psychometric theory: On the relation between process models for decision making and latent variable models for individual differences.

Maas

Molenaar

Maris

et al. 2011

Psychological Review

166

203

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This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics.

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“…Strandmark and Linn (1987) presented a 2PL model for person fit (see al.so Ferrando, 2007;Reise, 20(M)). Of interest, their 2PL model is similar to the D-diffusion item response model.…”

Section: (15)mentioning

confidence: 99%

Cognitive psychology meets psychometric theory: On the relation between process models for decision making and latent variable models for individual differences.

Maas

Molenaar

Maris

et al. 2011

Psychological Review

166

203

View full text Add to dashboard Cite

show abstract

“…For dichotomously scored items, the PRF provides the relationship between an examinee's probability of having a 1 score on an item as a function of the item's location. Lumsden (1978), Ferrando (2004Ferrando ( , 2007, and Emons et al (2005) noticed that the PRF based on the 1PLM decreases. Emons et al (2005) argued that a PRF that increases locally indicates misfit to the 1PLM and that the location of the increase in the PRF on the latent scale and also the shape of the PRF provide diagnostic information about misfit.…”

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confidence: 98%

“…For examinee v (we also use u and w as examinee indices), the PRF provides the relationship between the probability of a 1 score and the item location, •. Reise (2000) and Ferrando (2004Ferrando ( , 2007 defined a logistic PRF, which introduces a person parameter ' v in addition to ™ v . Parameter ' v quantifies the slope of the PRF for examinee v. Latent variable value ™ v is the location of the PRF of examinee v for which P v .•/ D :5.…”

Section: Person Response Functionmentioning

confidence: 99%

“…Parameter ' v quantifies the slope of the PRF for examinee v. Latent variable value ™ v is the location of the PRF of examinee v for which P v .•/ D :5. This PRF is defined as follows (Ferrando, 2004(Ferrando, , 2007Reise, 2000, p. 55):…”

Section: Person Response Functionmentioning

confidence: 99%

“…w D 0:2/ indicates a weak relation. Large negative slopes indicate high person reliability (Lumsden, 1977(Lumsden, , 1978, low individual trait variability (Ferrando, 2004(Ferrando, , 2007, and good person fit (Reise, 2000).…”

Section: Person Response Functionmentioning

confidence: 99%

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On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

Conijn

Emons

Assen

et al. 2011

Multivariate Behavioral Research

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The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this multilevel framework. An advantage of the multilevel framework is that it allows relating person fit to explanatory variables for person misfit/fit. We critically discuss Reise's approach. First, we argue that often the interpretation of the PRF slope as an indicator of person misfit is incorrect. Second, we show that the multilevel logistic regression model and the logistic PRF model are incompatible, resulting in a multilevel person-fit framework, which grossly violates the bivariate normality assumption for residuals in the multilevel model. Third, we use a Monte Carlo study to show that in the multilevel logistic regression framework estimates of distribution parameters of PRF intercepts and slopes are biased. Finally, we discuss the implications of these results and suggest an alternative multilevel regression approach to explanatory person-fit analysis. We illustrate the alternative approach using empirical data on repeated anxiety measurements of cardiac arrhythmia patients who had a cardioverter-defibrillator implanted.

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Item response and response time model for personality assessment via linear ballistic accumulation

Bunji

Okada

2019

Jpn J Stat Data Sci

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On the basis of a combination of linear ballistic accumulation (LBA) and item response theory (IRT), this paper proposes a new class of item response models, namely LBA IRT, which incorporates the observed response time by means of LBA. Our main objective is to develop a simple yet effective alternative to the diffusion IRT model, which is one of best-known response time (RT)-incorporating IRT models that explicitly models the underlying psychological process of the elicited item response. Through a simulation study, we show that the proposed model enables us to obtain the corresponding parameter estimates compared with the diffusion IRT model while achieving a much faster convergence speed. Furthermore, the application of the proposed model to real personality measurement data indicates that it fits the data better than the diffusion IRT model in terms of its predictive performance. Thus, the proposed model exhibits good performance and promising modeling capabilities in terms of capturing the cognitive and psychometric processes underlying the observed data.

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A Pearson-Type-VII item response model for assessing person fluctuation

Abstract: Personality measurement, item response theory, person response curve, expected a posteriori estimation, person reliability, scalability,

Cited by 16 publications

References 53 publications

Cognitive psychology meets psychometric theory: On the relation between process models for decision making and latent variable models for individual differences.

Cognitive psychology meets psychometric theory: On the relation between process models for decision making and latent variable models for individual differences.

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

Item response and response time model for personality assessment via linear ballistic accumulation

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