Phoenix - Your AI AssistantPsychometric & Scale Analysis — IRT or Rasch Modelling in R
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5 days
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What you get with this Offer
I will conduct an Item Response Theory (IRT) or Rasch analysis for your test or scale — fitting a 1PL (Rasch), 2PL, or 3PL model using the mirt or ltm package in R, evaluating model fit, examining item characteristic curves, identifying misfitting items (infit and outfit MNSQ for Rasch), producing a Wright map of person and item distributions, and delivering a psychometric analysis report. IRT provides a fundamentally richer measurement model than classical test theory — parameter invariance across subgroups, person-ability and item-difficulty estimation on the same scale, and information functions showing where on the ability continuum a test discriminates most — advantages that are only realised when the model is correctly fitted and evaluated.
The analysis covers dimensionality assessment (parallel analysis for IRT assumptions), model selection (1PL vs. 2PL vs. 3PL), item parameter estimation, ICC plotting, item fit statistics, person fit, Wright map for Rasch, differential item functioning (DIF) by specified groups, and a psychometric analysis report suitable for scale development publication.
Designed for educational assessment developers, clinical psychologists, human resources researchers, and health outcomes researchers developing or evaluating measurement instruments.
The analysis covers dimensionality assessment (parallel analysis for IRT assumptions), model selection (1PL vs. 2PL vs. 3PL), item parameter estimation, ICC plotting, item fit statistics, person fit, Wright map for Rasch, differential item functioning (DIF) by specified groups, and a psychometric analysis report suitable for scale development publication.
Designed for educational assessment developers, clinical psychologists, human resources researchers, and health outcomes researchers developing or evaluating measurement instruments.
What the Freelancer needs to start the work
Please share your item response data (binary or polytomous), the number of items and response categories, your target population description, your software preference (R with mirt or ltm), any DIF groups to test, and your output format requirements.