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Contents
- ability
- The ability estimates
- ability estimates
- Step 4 : the
| The ability estimates
- aggregated
- The data aggregation
- algorithms
- The algorithm
- all the data points from the plots
- Step 4 : the
- asymptote
- The three parameters logistic
| The item parameter
- asymptote mean
- The asymptote prior
- asymptote weight
- The asymptote prior
- back
- Assistant usage
- bandwidth
- The kernel smoothing factor
- binary
- The one parameter logistic
| The two parameters logistic
| The three parameters logistic
- binary type
- Binary type
- cancel
- Assistant usage
- Chi-square
- The test of fit
| The test of local
- classical test theory statistics
- The classical test theory
- converged
- The estimation summary
- correction key
- Step 1 : the
| Multiple choice type
- correlation (discrimination)
- The classical test theory
- Cronbach's alpha
- The classical test theory
| The classical test theory
- data source
- The estimation summary
- data type
- Step 2 : the
- degree of freedom
- The test of fit
| The test of local
- delete a sheet
- The report
- difficulties
- The classical test theory
- difficulty
- The one parameter logistic
- discrimination
- The one parameter logistic
- discriminations
- The classical test theory
- display language
- Installation
| The language
- edit
- The report
- eirt
- Assistant usage
| The report
| Settings
- estimation methode
- The estimation summary
- first middle point
- The first middle point
- graded
- The nominal response model
| The nominal response model
| The graded response model
- graded response model
- The nominal response model
| The graded response model
- graded type
- Graded type
- guessing
- The three parameters logistic
- help
- Assistant usage
- ICC
- The item and option
| All the data points
- ignored
- The estimation summary
- information functions
- The information functions
| The information functions
| All the data points
- installation language
- Installation
- installation program
- Installation
- item and option characteristic curves
- The item and option
- item correlation
- The classical test theory
- item labels
- Step 1 : the
- item means
- The classical test theory
- item parameters
- The item parameters
- kernel estimator
- The kernel estimator
- last middle point
- The last middle point
- macro activation
- Installation
- mean (difficulty)
- The classical test theory
- minimal
- Graded type
- missing values
- Step 2 : the
- model
- Step 3 : the
| The estimation summary
- multiple choice
- The nominal response model
- multiple choice type
- Multiple choice type
- next
- Assistant usage
- nominal response model
- The nominal response model
- number of item
- The classical test theory
- number of iteration
- The number of EM
| The number of Newton
- number of missing value
- The classical test theory
- number of quadrature
- The number of quadrature
- number of subject
- The classical test theory
- OCC
- The item and option
| All the data points
- ok
- Settings
- one parameter logistic model
- The one parameter logistic
- p-value
- The test of fit
| The test of local
- penalization
- The penalization smoothing factor
- penalized maximum marginal likelihood estimator
- The penalized maximum marginal
- precision
- The precision
- prior distributions
- The priors
- quadratures
- The quadratures
- s.e.
- The item parameter
| The ability estimates
- save
- The report
- score mean
- The classical test theory
- score standard deviation
- The classical test theory
- selection
- Step 1 : the
- settings
- Installation
| Settings
| Settings
- slope
- The one parameter logistic
| The two parameters logistic
| The three parameters logistic
| The nominal response model
| The graded response model
| The item parameter
- slope mean
- The slope prior
- slope standard deviation
- The slope prior
- smoothing parameter
- The estimation summary
- standard deviation
- The classical test theory
- standard error
- The item parameter
| The ability estimates
- standard errors
- The standard errors
- start the assistant
- Assistant usage
- subject labels
- Step 1 : the
- succes
- Binary type
- test of fit
- The test of fit
- test of local independance
- Step 4 : the
| The test of local
- three parameters logistic model
- The three parameters logistic
- threshold
- The one parameter logistic
| The two parameters logistic
| The three parameters logistic
| The nominal response model
| The graded response model
| The item parameter
- threshold mean
- The threshold prior
- threshold standard deviation
- The threshold prior
- tools
- Assistant usage
| Settings
- two parameters logistic model
- The two parameters logistic
2011-09-23