PerFit (version 1.3.1)

summary PerFit: Summary method for objects of class "PerFit"

Description

Summary method for objects of class "PerFit".

Usage

## S3 method for class 'PerFit':
summary(object, cutoff.obj=NULL, 
        ModelFit="NonParametric", Nreps=1000, 
        IP=object$IP, IRT.PModel=object$IRT.PModel, Ability=object$Ability,
        Ability.PModel=object$Ability.PModel, mu=0, sigma=1, 
        Blvl = 0.05, Breps = 1000, CIlvl = 0.95, 
        UDlvl = NA, ...)

Arguments

object

Object of class "PerFit".

cutoff.obj

Object of class "PerFit.cutoff".

ModelFit

Method required to compute model-fitting item score patterns. The options available are "NonParametric" (default) and "Parametric".

Nreps

Number of model-fitting item score patterns generated. Default is 1000.

IP

Matrix with previously estimated item parameters. Default is object$IP.

IRT.PModel

Parametric IRT model (required if "ModelFit=Parametric" or if the person fit statistic is parametric). Default is object$IRT.PModel.

Ability

Matrix with previously estimated item parameters. Default is object$Ability.

Ability.PModel

Method to use in order to estimate the latent ability parameters (required if "ModelFit=Parametric" or if the person fit statistic is parametric). Default is object$Ability.PModel.

mu

Mean of the apriori distribution. Only used when method="BM". Default is 0.

sigma

Standard deviation of the apriori distribution. Only used when method="BM". Default is 1.

Blvl

Significance level for bootstrap distribution (value between 0 and 1). Default is 0.05.

Breps

Number of bootstrap resamples. Default is 1000.

UDlvl

User-defined cutoff level.

CIlvl

Level of bootstrap percentile confidence interval for the cutoff statistic.

...

Additional arguments to be passed to summary.

Details

For a given object of class PerFit, this function prints: The PFS used, the cutoff value, the tail of the distribution of the person-fit statistic associated to misfit, the proportion of flagged respondents in the sample, and their row indices.

See Also

cutoff, flagged.resp, plot.PerFit, summary.PerFit

Examples

# Load the inadequacy scale data (dichotomous item scores):
data(InadequacyData)

# Compute the ZU3 scores:
ZU3.out <- ZU3(InadequacyData)

summary(ZU3.out)