Package Overview
The wizirt package (currently named wizirt2) is up and running, it seems to work for different data sets. It has a limited functionality, but it is currently working.
The wizirt package represents the work of my dissertation. As such I have agreed to do the following for my dissertation:
- Provide general model information including:
- Model call
- Description of model run
- Software and version
- Estimator
- Convergence status, criteria, values
- Estimation issues
- Response data described (sample size, demographics)
- Descriptions of items and test
- Missing data summary
- Description of missing data handling
- Provide model fit information
- Unidimensionality (DETECT)
- Absolute fit
- Relative fit
- Anova method for comparing models
- Provide item information
- Parameter estimates
- Summary statistics
- Provide item-fit information
- Conditional dependence
- Functional form (isn’t this model-data fit?)
- Fit statistics
- predicted vs observed item response functions
- misfitting items flagged
- Provide person information
- Person location estimates (including SE)
- Provide person-fit information
- Global detection (Ht, lz*, infit and outfit, with cutoffs where applicable)
- Local detection (ICI or other)
- Tabulation or presentation of response patterns (winsteps tables as guides)
- PRF (nonparametric, parametric may follow later)
- MLM (Reise, Conijn)
- Two levels of accessibility
- Comprehensive report for beginners
- Felxible functions for advanced users
- Learning Resources
- Github website
- CRAN-style reference page
- tidyverse-style cheat sheet
- Karabatsos’s simulation replication article
- Quality Assurance
- Accuracy check
- Match IRTPRO, Winsteps
- Replicate Karabatsos
- Informative check (meet all the checks above two levels…)
- Usefulness check
- Usability testing
- Call it from python on separate laptop
- Aesthetics check
- Repetition
- Contrast
- Alignment
- Proximity
My goal is to complete all of this by October 24. That will give me a week to write it all up by October 30 and give it to my chair. Then I will have a week to improve it according to my chair’s recommendations so I can send it to my committee by November 6.