Score‐based measurement invariance checks for Bayesian maximum‐a‐posteriori estimates in item response theory

A family of score-based tests has been proposed in recent years for assessing the invariance of model parameters in several models of item response theory (IRT). These tests were originally developed in a maximum likelihood framework. This study discusses analogous tests for Bayesian maximum-a-posteriori estimates and multiple-group IRT models. We propose two families of statistical tests, which are based on an approximation using a pooled variance method, or on a simulation approach based on asymptotic results. The resulting tests were evaluated by a simulation study, which investigated their sensitivity against differential item functioning with respect to a categorical or continuous person covariate in the two- and three-parametric logistic models. Whereas the method based on pooled variance was found to be useful in practice with maximum likelihood as well as maximum-a-posteriori estimates, the simulation-based approach was found to require large sample sizes to lead to satisfactory results

Development and validation of a patient-reported outcome measure for systemic sclerosis: the EULAR Systemic Sclerosis Impact of Disease (ScleroID) questionnaire

OBJECTIVES: Patient-reported outcome measures (PROMs) are important for clinical practice and research. Given the high unmet need, our aim was to develop a comprehensive PROM for systemic sclerosis (SSc), jointly with patient experts. METHODS: This European Alliance of Associations for Rheumatology (EULAR)-endorsed project involved 11 European SSc centres. Relevant health dimensions were chosen and prioritised by patients. The resulting Systemic Sclerosis Impact of Disease (ScleroID) questionnaire was subsequently weighted and validated by Outcome Measures in Rheumatology criteria in an observational cohort study, cross-sectionally and longitudinally. As comparators, SSc-Health Assessment Questionnaire (HAQ), EuroQol Five Dimensional (EQ-5D), Short Form-36 (SF-36) were included. RESULTS: Initially, 17 health dimensions were selected and prioritised. The top 10 health dimensions were selected for the ScleroID questionnaire. Importantly, Raynaud's phenomenon, impaired hand function, pain and fatigue had the highest patient-reported disease impact. The validation cohort study included 472 patients with a baseline visit, from which 109 had a test-retest reliability visit and 113 had a follow-up visit (85% female, 38% diffuse SSc, mean age 58 years, mean disease duration 9 years). The total ScleroID score showed strong Pearson correlation coefficients with comparators (SSc-HAQ, 0.73; Patient's global assessment, Visual Analogue Scale 0.77; HAQ-Disability Index, 0.62; SF-36 physical score, -0.62; each p<0.001). The internal consistency was strong: Cronbach's alpha was 0.87, similar to SSc-HAQ (0.88) and higher than EQ-5D (0.77). The ScleroID had excellent reliability and good sensitivity to change, superior to all comparators (intraclass correlation coefficient 0.84; standardised response mean 0.57). CONCLUSIONS: We have developed and validated the EULAR ScleroID, which is a novel, brief, disease-specific, patient-derived, disease impact PROM, suitable for research and clinical use in SSc

Graphene -- Based Nanocomposites as Highly Efficient Thermal Interface Materials

We found that an optimized mixture of graphene and multilayer graphene - produced by the high-yield inexpensive liquid-phase-exfoliation technique - can lead to an extremely strong enhancement of the cross-plane thermal conductivity K of the composite. The "laser flash" measurements revealed a record-high enhancement of K by 2300 % in the graphene-based polymer at the filler loading fraction f =10 vol. %. It was determined that a relatively high concentration of single-layer and bilayer graphene flakes (~10-15%) present simultaneously with thicker multilayers of large lateral size (~ 1 micrometer) were essential for the observed unusual K enhancement. The thermal conductivity of a commercial thermal grease was increased from an initial value of ~5.8 W/mK to K=14 W/mK at the small loading f=2%, which preserved all mechanical properties of the hybrid. Our modeling results suggest that graphene - multilayer graphene nanocomposite used as the thermal interface material outperforms those with carbon nanotubes or metal nanoparticles owing to graphene's aspect ratio and lower Kapitza resistance at the graphene - matrix interface.Comment: 4 figure

Score-Based Tests with Fixed Effects Person Parameters in Item Response Theory: Detecting Model Misspecification Including Differential Item Functioning

We adapt score-based tests for item response theory models that treat the person parameters as fixed effects, which are important for large data and item counts where typical approaches can be too slow. Our adaptation allows fast tests for differential item function and other model misspecifications, in that score contributions are leveraged and comparison models are not required. We outline the theoretical framework and adapt it to two recently proposed consistent methods of parameter estimation, constrained joint maximum likelihood estimation and a joint maximum a posteriori approach. A key benefit of the approach is that, in contrast to earlier score-based test approaches, the prior for person parameters does not need to be specified precisely. We use simulations to evaluate the new method for detecting violations of measurement invariance in the two-parametric logistic test model. The new method is sensitive to violations of measurement invariance while having a sufficiently low Type I error rate in large samples and tests. We demonstrate the new method in an empirical data set examining reading performance, from the Mindsteps online learning platform

Score-Based Measurement Invariance Checks for Bayesian Maximum-a-Posteriori Estimates in Item Response Theory

A family of score-based tests has been proposed in the past years for assessing the invariance of model parameters in several models of item response theory. These tests were originally developed in a maximum likelihood framework. This study aims to extend the theoretical framework of these tests to Bayesian maximum-a-posteriori estimates and to multiple group IRT models. We propose two families of statistical tests, which are based on a) an approximation using a pooled variance method, or b) a simulation-based approach based on asymptotic results. The resulting tests were evaluated by a simulation study, which investigated their sensitivity against differential item functioning with respect to a categorical or continuous person covariate in the two- and three-parametric logistic models. Whereas the method based on pooled variance was found to be practically useful with maximum likelihood as well as maximum-a-posteriori estimates, the simulation-based approach was found to require large sample sizes to lead to satisfactory results

Model Selection of Nested and Non-Nested Item Response Models Using Vuong Tests

In this paper, we apply Vuong's general approach of model selection to the comparison of nested and non-nested unidimensional and multidimensional item response theory (IRT) models. Vuong's approach of model selection is useful because it allows for formal statistical tests of both nested and non-nested models. However, only the test of non-nested models has been applied in the context of IRT models to date. After summarizing the statistical theory underlying the tests, we investigate the performance of all three distinct Vuong tests in the context of IRT models using simulation studies and real data. In the non-nested case we observed that the tests can reliably distinguish between the graded response model and the generalized partial credit model. In the nested case, we observed that the tests typically perform as well as or sometimes better than the traditional likelihood ratio test. Based on these results, we argue that Vuong's approach provides a useful set of tools for researchers and practitioners to effectively compare competing nested and non-nested IRT models