Article2015

A flexible full-information approach to the modeling of response styles.

123 citations0/0 files storedPsychological Methods

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Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Mental Health Research Topics

Abstract

We present a flexible full-information approach to modeling multiple user-defined response styles across multiple constructs of interest. The model is based on a novel parameterization of the multidimensional nominal response model that separates estimation of overall item slopes from the scoring functions (indicating the order of categories) for each item and latent trait. This feature allows the definition of response styles to vary across items as well as overall item slopes that vary across items for both substantive and response style dimensions. We compared the model with similar approaches using examples from the smoking initiative of the Patient-Reported Outcomes Measurement Information System. A small set of simulations showed that the estimation approach is able to recover model parameters, factor scores, and reasonable estimates of standard errors. Furthermore, these simulations suggest that failing to include response style factors (when present in the data generating model) has adverse consequences for substantive trait factor score recovery. (PsycINFO Database Record

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References

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Cited by

2019Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations 2021Incremental Model Fit Assessment in the Case of Categorical Data: Tucker–Lewis Index for Item Response Theory Modeling 2016Measurement and control of bias in patient reported outcomes using multidimensional item response theory 2016Mountain or Molehill? A Simulation Study on the Impact of Response Styles 2020Different approaches to modeling response styles in divide-by-total item response theory models (part 1): A model integration.

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