Search Results (6)

This study investigates the performance of estimation methods for multidimensional IRT models with dichotomous and polytomous data in two well-known IRT programs: SAS PROC IRT and the mirt package in R. A simulation study was used to compare performance on a simple structure Rasch model, complex structure 2PL model, and bifactor graded response model. Under RMSE and bias criteria regarding item parameter recovery, PROC IRT and mirt showed nearly identical performance in the simple structure condition. When a complex structure was used, mirt performed better in terms of the recovery of intercept parameters, while the recovery of slope parameters depended on the program and the sample sizes: PROC IRT tended to be better with small samples ($N=500$) according to RMSE, and mirt was better for larger samples ($N=1000$ and $2500$) according to RMSE and bias for the slope parameter recovery. When a bifactor structure was used, mirt was preferred in all cases; differences lessened as sample size increased. Full article

Background: The Schizophrenia Coping Oral Health Profile and Index (SCOOHPI) scale studies the coping strategies of schizophrenic patients with regard to oral health. The structural validity of this scale is studied has been studied using factor analyses. In this article, we study the unidimensionality of the SCOOHPI scale to use it as an index. Methods: We studied the internal consistency of the items of the SCOOHPI scale. Then, we studied the construct validity. The unidimensionality of the SCOOHPI scale was studied by the partial credit model. Results: The data used in this study come from five hospitals, and the total number of individuals participating in this study is 96, of which 72% are men and 59% are smokers. The SCOOHPI scale has good internal consistency (α = 0.84). The validity of divergence was checked by the absence of correlation between the SCOOHPI scale and the GOHAI (General Oral Health Assessment Index) scale. The unidimensionality of the SCOOHPI scale with data smoothing was demonstrated by the partial credit model. Conclusion: In this study, we completed the study of the psychometric validation of the SCOOHPI. The SCOOHPI scale can then contribute to improving evaluation of the coping strategies of schizophrenic patients with regard to oral health. Full article

Explanatory item response modeling (EIRM) enables researchers and practitioners to incorporate item and person properties into item response theory (IRT) models. Unlike traditional IRT models, explanatory IRT models can explain common variability stemming from the shared variance among item clusters and person groups. In this tutorial, we present the R package eirm, which provides a simple and easy-to-use set of tools for preparing data, estimating explanatory IRT models based on the Rasch family, extracting model output, and visualizing model results. We describe how functions in the eirm package can be used for estimating traditional IRT models (e.g., Rasch model, Partial Credit Model, and Rating Scale Model), item-explanatory models (i.e., Linear Logistic Test Model), and person-explanatory models (i.e., latent regression models) for both dichotomous and polytomous responses. In addition to demonstrating the general functionality of the eirm package, we also provide real-data examples with annotated R codes based on the Rosenberg Self-Esteem Scale. Full article

The fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is an attractive tool for measuring complex phenomena based on uncertain data. The original version of the method assumes that the object assessments in terms of the adopted criteria are expressed as triangular fuzzy numbers. One of the crucial stages of the fuzzy TOPSIS is selecting the fuzzy conversion scale, which is used to evaluate objects in terms of the adopted criteria. The choice of a fuzzy conversion scale may influence the results of the fuzzy TOPSIS. There is no uniform approach in constructing and selecting the fuzzy conversion scale for the fuzzy TOPSIS. The choice is subjective and made by researchers. Therefore, the aim of the article is to present a new, objective approach to the construction of fuzzy conversion scales based on Item Response Theory (IRT) models. The following models were used in the construction of fuzzy conversion scales: Polychoric Correlation Model (PM), Polytomous Rasch Model (PRM), Rating Scale Model (RSM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), Graded Response Model (GRM), Nominal Response Model (NRM). The usefulness of the proposed approach is presented on the example of the analysis of a survey’s results on measuring the quality of professional life of inhabitants of selected communes in Poland. The obtained results indicate that the choice of the fuzzy conversion scale has a large impact on the closeness coefficient values. A large difference was also observed in the spreads of triangular fuzzy numbers between scales based on IRT models and those used in the literature on the subject. The use of the fuzzy TOPSIS with fuzzy conversion scales built based on PRM, RSM, PCM, GPCM, and GRM models gives results with a greater range of variability than in the case of fuzzy conversion scales used in empirical research. Full article

The usual approach in disability surveys is to screen persons with disability upfront and then ask questions about everyday problems. The objectives of this paper are to demonstrate the impact of screeners on disability rates, to challenge the usual exclusion of persons with mild and moderate disability from disability surveys and to demonstrate the advantage of using an a posteriori cut-off. Using data of a pilot study of the WHO Model Disability Survey (MDS) in Cambodia and the polytomous Rasch model, metric scales of disability were built. The conventional screener approach based on the short disability module of the Washington City Group and the a posteriori cut-off method described in the World Disability Report were compared regarding disability rates. The screener led to imprecise rates and classified persons with mild to moderate disability as non-disabled, although these respondents already experienced important problems in daily life. The a posteriori cut-off applied to the general population sample led to a more precise disability rate and allowed for a differentiation of the performance and needs of persons with mild, moderate and severe disability. This approach can be therefore considered as an inclusive approach suitable to monitor the Convention on the Rights of Persons with Disabilities. Full article

Background: Reliable and valid assessment of the disease burden across all forms of cancer is critical to the evaluation of treatment effectiveness and patient progress. The Edmonton Symptom Assessment System (esas) is used for routine evaluation of people attending for cancer care. In the present study, we used Rasch analysis to explore the measurement properties of the esas and to determine the effect of using Raschproposed interval-level esas scoring compared with traditional scoring when evaluating the effects of an exercise program for cancer survivors. Methods: Polytomous Rasch analysis (Andrich’s rating-scale model) was applied to data from 26,645 esas questionnaires completed at the Juravinski Cancer Centre. The fit of the esas to the polytomous Rasch model was investigated, including evaluations of differential item functioning for sex, age, and disease group. The research implication was investigated by comparing the results of an observational research study previously analysed using a traditional approach with the results obtained by Rasch-proposed interval-level esas scoring. Results: The Rasch reliability index was 0.73, falling short of the desired 0.80–0.90 level. However, the esas was found to fit the Rasch model, including the criteria for uni-dimensional data. The analysis suggests that the current esas scoring system of 0–10 could be collapsed to a 6-point scale. Use of the Rasch-proposed interval-level scoring yielded results that were different from those calculated using summarized ordinallevel esas scores. Differential item functioning was not found for sex, age, or diagnosis groups. Conclusions: The esas is a moderately reliable uni-dimensional measure of cancer disease burden and can provide interval-level scaling with Rasch-based scoring. Further, our study indicates that, compared with the traditional scoring metric, Rasch-based scoring could result in substantive changes to conclusions. Full article