Full-Information Item Bifactor Analysis of Graded Response Data
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چکیده
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منابع مشابه
Generalized full-information item bifactor analysis.
Full-information item bifactor analysis is an important statistical method in psychological and educational measurement. Current methods are limited to single-group analysis and inflexible in the types of item response models supported. We propose a flexible multiple-group item bifactor analysis framework that supports a variety of multidimensional item response theory models for an arbitrary m...
متن کاملFull-Information Item Bifactor Analysis of the Job Burnout Scale for Chinese College Teachers
The bifactor structure has been considered a credible model for various types of data. Research purposes were: (a) to test the utility of the bifactor IRT model for dimensionality assessment and (b) to confirmatory factor analyze the structure of the newly-developed scale, the Job Burnout Scale for Chinese College Teachers. 1331 teachers were chosen from 11 various Universities in China. 1111(8...
متن کاملThe Coexistence of Coping Resources and Specific Coping Styles in Stress: Evidence from Full Information Item Bifactor Analysis
BACKGROUND Knowledge of coping styles is useful in clinical diagnosis and suggesting specific therapeutic interventions. However, the latent structures and relationships between different aspects of coping styles have not been fully clarified. A full information item bifactor model will be beneficial to future research. OBJECTIVE One goal of this study is identification of the best fit statis...
متن کاملBifactor Item Response Theory Model of Acute Stress Response
BACKGROUND Better understanding of acute stress responses is important for revision of DSM-5. However, the latent structure and relationship between different aspects of acute stress responses haven't been clarified comprehensively. Bifactor item response model may help resolve this problem. OBJECTIVE The purpose of this study is to develop a statistical model of acute stress responses, based...
متن کاملBifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores.
The application of psychological measures often results in item response data that arguably are consistent with both unidimensional (a single common factor) and multidimensional latent structures (typically caused by parcels of items that tap similar content domains). As such, structural ambiguity leads to seemingly endless "confirmatory" factor analytic studies in which the research question i...
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