How many IRT parameters does it take to model psychopathology items?

Reise, Steven P.; Waller, Niels G.

doi:10.1037/1082-989x.8.2.164

Cited by 103 publications

(144 citation statements)

References 35 publications

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“…We thus fully agree with a remark made in Reise and Waller (2003) that "the process of IRT fit assessment and model comparison can be viewed more as a way of learning about item and test functioning than as a process of mere statistical decision making" (p. 180). Using different models and different methods of analysis forces a researcher to think about his or her decisions and also prevents a researcher from relying on the default options found in many statistical packages.…”

Section: Discussionsupporting

confidence: 88%

“…In personality measurement the 2PLM (or its polytomous extension, the graded response model) is often applied because it is assumed that persons do not guess on the items. However, in a recent study by Reise and Waller (2003) new insights were obtained about the psychometric characteristics of psychopathology data. They compared the fit of the 2PLM and 3PLM on 15 unidimensional factor scales from the MMPI-A item pool.…”

Section: Parametric Irt Modelsmentioning

confidence: 99%

“…On the basis of the results of Reise and Waller (2003), we expected that for items with a non-zero lower asymptote the estimated discrimination parameter will be smaller under the 2PLM than under the 3PLM, and for the items with a non-one upper asymptote we expected that the estimated parameters will be similar under the 2PLM and the 3PLM, but lower relative to the 3PLM with reversed keying (3PLM-R). This was confirmed in our data analysis.…”

Section: Investigating Monotonicitymentioning

confidence: 99%

“…For example, Waller, Tellegen, McDonald, and Lykken (1996) contrasted the use of IRT with principalcomponent factor analysis, and Reise and Waller (2003) discussed the choice of an IRT model to analyze psychopathology-test data. That is, they compared the fit of the two-parameter and three-parameter logistic models (PLMs) on 15 unidimensional factor scales from the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A; Butcher et al, 1992).…”

mentioning

confidence: 99%

“…First, we introduce the basic principles of parametric IRT and NIRT in relation to the analysis of personality data. In particular we focus on recent results discussed in Reise and Waller (2003), because their results suggest that besides the use of parametric IRT models, NIRT models are useful to analyze personality data. Second, we introduce nonparametric fit methods for two NIRT models without going into technical detail.…”

mentioning

confidence: 99%

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Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Meijer

Baneke

2004

Psychological Methods

190

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The authors discuss the applicability of nonparametric item response theory (IRT) models to the construction and psychometric analysis of personality and psychopathology scales, and they contrast these models with parametric IRT models. They describe the fit of nonparametric IRT to the Depression content scale of the Minnesota Multiphasic Personality Inventory-2 (J. N. Butcher, W. G. Dahlstrom, J. R. Graham, A. Tellegen, & B. Kaemmer, 1989). They also show how nonparametric IRT models can easily be applied and how misleading results from parametric IRT models can be avoided. They recommend the use of nonparametric IRT modeling prior to using parametric logistic models when investigating personality data.Recently, several authors have introduced and discussed the advantages of applying item response theory (IRT) models (e.g., Embretson & Reise, 2000) to construct personality 1 scales and to explore the structure of personality data sets. For example, Waller, Tellegen, McDonald, and Lykken (1996) contrasted the use of IRT with principalcomponent factor analysis, and Reise and Waller (2003) discussed the choice of an IRT model to analyze psychopathology-test data. That is, they compared the fit of the two-parameter and three-parameter logistic models (PLMs) on 15 unidimensional factor scales from the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A; Butcher et al., 1992). Most studies apply parametric IRT models (in particular, the 2PLM and 3PLM) to investigate the quality of personality and psychopathology tests (e.g., Panter, Swygert, Dahlstrom, & Tanake, 1997;Robie, Zickar, & Schmitt, 2001;Steinberg, 1994;Waller, Thompson, & Wenk, 2000).The aim of the present study was to illustrate the usefulness of nonparametric IRT (NIRT) to construct and to analyze psychopathology and personality scales and tests. In our opinion, the use of NIRT has been underexposed in the recent personality literature (for an exception, see Santor & Ramsay, 1998). We show that these models are very suitable to exploring the psychometric properties of personality data. Interesting in this context is a study by Chernyshenko, Stark, Chan, Drasgow, and Williams (2001), who explored the use of NIRT modeling in personality measurement. Chernyshenko et al. fitted the 2PLM, the 3PLM, a graded response model, and Levine's nonparametric maximum-likelihood formula scoring models to dichotomous and polytomous data of the Sixteen Personality Factor Questionnaire (Conn & Rieke, 1994). They concluded that the nonparametric model provided the best fit of the models considered. Chernyshenko et al. and also Reise and Waller (2003) concluded that the response process underlying personality measurement is less well-understood than the response process in the cognitive domain. This being the case, we argue that using NIRT models based on exploring the simple covariance structure between items and based on nonparametric regression will lead to useful information that (a) can be interpreted very easily by practitioners, (b) avoids forcing the data ...

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Section: Discussionsupporting

confidence: 88%

Section: Parametric Irt Modelsmentioning

confidence: 99%

Section: Investigating Monotonicitymentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Meijer

Baneke

2004

Psychological Methods

190

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Item Response Theory, Approach to Test Construction

Lutz

Embretson

2015

The Encyclopedia of Clinical Psychology

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Item response theory (IRT) has had a major impact on instrument design and analysis, both in academic and clinical settings. This entry provides an introduction to the common dichotomous and polytomous IRT models and motivates the use of IRT in the test design process by comparing it with the previously dominant classical test theory. This entry provides a brief introduction to IRT to provide a foundation for the reader to develop a functional instrument within the IRT framework.

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What does the beck depression inventory measure in myocardial infarction patients? a psychometric approach using item response theory and person‐fit

Wardenaar

Wanders

Roest

et al. 2015

Int J Methods Psych Res

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Observed associations between depression following myocardial infarction (MI) and adverse cardiac outcomes could be overestimated due to patients' tendency to over report somatic depressive symptoms. This study was aimed to investigate this issue with modern psychometrics, using item response theory (IRT) and person-fit statistics to investigate if the Beck Depression Inventory (BDI) measures depression or something else among MI-patients. An IRT-model was fit to BDI-data of 1135 MI patients. Patients' adherence to this IRT-model was investigated with person-fit statistics. Subgroups of "atypical" (low person-fit) and "prototypical" (high person-fit) responders were identified and compared in terms of item-response patterns, psychiatric diagnoses, socio-demographics and somatic factors. In the IRT model, somatic items had lower thresholds compared to depressive mood/cognition items. Empirically identified "atypical" responders (n = 113) had more depressive mood/cognitions, scored lower on somatic items and more often had a Comprehensive International Diagnostic Interview (CIDI) depressive diagnosis than "prototypical" responders (n = 147). Additionally, "atypical" responders were younger and more likely to smoke. In conclusion, the BDI measures somatic symptoms in most MI patients, but measures depression in a subgroup of patients with atypical response patterns. The presented approach to account for interpersonal differences in item responding could help improve the validity of depression assessments in somatic patients.

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How many IRT parameters does it take to model psychopathology items?

Cited by 103 publications

References 35 publications

Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Item Response Theory, Approach to Test Construction

What does the beck depression inventory measure in myocardial infarction patients? a psychometric approach using item response theory and person‐fit

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