summary.mdf: `summary` method for S3 class `"mdf"` objects.

Description

Generic function that is used in order to summarize information from "mdf" class objects.

Usage

# S3 method for mdf
summary(object, boot=FALSE, type="perc", ...)

Value

The output of the summary.mdf() is a list with two main components. The first component of the list is a data.frame with scale statistics and the second component is a list with item statistics. If diagnostics=TRUE another component with diagnostic matrices is also included in the output. When the bootstrap scale estimate does not agree with the obtained MUDFOLD estimate a summary of the bootstrap scale will be given in the output.

Arguments

object: : Object of class "mdf" resulted from the function mudfold or as.mudfold.
boot: : This argument applies when the nboot argument in the mudfold function is not NULL. If boot=FALSE (default) then no bootstrap information is returned by the summary. When boot=TRUE, confidence intervals, standard errors, biases, calculated from the bootstrap iterations for each parameter are given with the output. If the bootstrap estimate of the scale does not agree with the the scale of the item selection algorithm, then a summary of the bootstrap estimate of the scale is also given in the output.
type: : A string that determines the type of confidence intervals that will be calculated. This argument is passed to the boot.ci function from the R package boot. Available options are c("norm","basic", "perc", "bca"). See ?boot.ci for more information.
...: Other arguments passed on to the function boot.ci from the R package boot.

Author

Spyros E. Balafas (auth.), Wim P. Krijnen (auth.), Wendy J. Post (contr.), Ernst C. Wit (auth.)

Maintainer: Spyros E. Balafas (s.balafas@rug.nl)

Details

A summary of the MUDFOLD scale that has been calculated with the mudfold function.

References

W.H. Van Schuur.(1984). Structure in Political Beliefs: A New Model for Stochastic Unfolding with Application to European Party Activists. CT Press.

W.J. Post. (1992). Nonparametric Unfolding Models: A Latent Structure Approach. M & T series. DSWO Press.

W.J. Post. and T.AB. Snijders (1993). Nonparametric unfolding models for dichotomous data. Methodika.

Examples

Run this code

if (FALSE) {
data(ANDRICH)
fit <- mudfold(ANDRICH, nboot=100)
summary(fit, boot=TRUE)
summary(fit, boot=FALSE)

}

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