prob.guttman.Rd
This function estimates the probabilistic Guttman model which is a special case of an ordered latent trait model (Hanson, 2000; Proctor, 1970).
prob.guttman(dat, pid=NULL, guess.equal=FALSE, slip.equal=FALSE, itemlevel=NULL, conv1=0.001, glob.conv=0.001, mmliter=500) # S3 method for prob.guttman summary(object,...) # S3 method for prob.guttman anova(object,...) # S3 method for prob.guttman logLik(object,...) # S3 method for prob.guttman IRT.irfprob(object,...) # S3 method for prob.guttman IRT.likelihood(object,...) # S3 method for prob.guttman IRT.posterior(object,...)
dat | An \(N \times I\) data frame of dichotomous item responses |
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pid | Optional vector of person identifiers |
guess.equal | Should the same guessing parameters for all the items estimated? |
slip.equal | Should the same slipping parameters for all the items estimated? |
itemlevel | A vector of item levels of the Guttman scale for each item. If there are \(K\) different item levels, then the Guttman scale possesses \(K\) ordered trait values. |
conv1 | Convergence criterion for item parameters |
glob.conv | Global convergence criterion for the deviance |
mmliter | Maximum number of iterations |
object | Object of class |
... | Further arguments to be passed |
An object of class prob.guttman
Estimated person parameters
Estimated item parameters
Ability levels
Estimated trait distribution
Information criteria
Deviance
Number of iterations
Specified allocation of items to trait levels
Hanson, B. (2000). IRT parameter estimation using the EM algorithm. Technical Report.
Proctor, C. H. (1970). A probabilistic formulation and statistical analysis for Guttman scaling. Psychometrika, 35, 73-78.