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eirt - Item Response Theory Assistant for Excel
Stéphane Germain, Pierre Valois and Belkacem Abdous
september 7 2007
Contents
Introduction
Installation
Assistant usage
Step 1 : the data selection
Step 2 : the data type definition
Binary type
Multiple choice type
Graded type
Step 3 : the model or method choice
The one parameter logistic model
The two parameters logistic model
The three parameters logistic model
The nominal response model
The graded response model
The kernel estimator
The penalized maximum marginal likelihood estimator
Step 4 : the report options
The classical test theory statistics
The test of fit
The test of local independance
The item parameters
The ability estimates
The item and option characteristic curves
The information functions
The standard errors
All the data points from the plots
The report
The classical test theory statistics
The estimation summary
The test of fit
The test of local independance
The item parameter
The ability estimates
The item and option characteristic curves
The information functions
All the data points from the plots
The pages header and footer
Settings
The language
The priors
The slope prior
The threshold prior
The asymptote prior
The algorithm
The number of EM iteration
The number of Newton iteration
The precision
The kernel smoothing factor
The penalization smoothing factor
The data aggregation
The quadratures
The number of quadrature
The first middle point
The last middle point
Copyright
Index
About this document ...
2011-09-23
