ltm (version 0.8-9)

summary: Summary method for fitted IRT models

Description

Summarizes the fit of either grm, ltm, rasch or tpm objects.

Usage

## S3 method for class 'grm':
summary(object, \dots)

## S3 method for class 'ltm':
summary(object, robust.se = FALSE, \dots)

## S3 method for class 'rasch':
summary(object, robust.se = FALSE, \dots)

## S3 method for class 'tpm':
summary(object, \dots)

Arguments

object

an object inheriting from either class grm, class ltm, class rasch or class tpm.

robust.se

logical; if TRUE robust estimation of standard errors is used, based on the sandwich estimator.

...

additional argument; currently none is used.

Value

• An object of either class summ.grm, class summ.ltm or class summ.rasch with components,
• coefficients
  the estimated coefficients' table.
• Var.betas
  the approximate covariance matrix for the estimated parameters; returned only in summ.ltm and summ.rasch.
• logLik
  the log-likelihood of object.
• AIC
  the AIC for object.
• BIC
  the BIC for object.
• max.sc
  the maximum absolute value of the score vector at convergence.
• conv
  the convergence identifier returned by optim().
• counts
  the counts argument returned by optim().
• call
  the matched call of object.
• ltn.struct
  a character vector describing the latent structure used in object; returned only in summ.ltm.
• control
  the values used in the control argument in the fit of object.
• nitems
  the number of items in the data set; returned only in summ.ltm and summ.rasch.

See Also

grm, ltm, rasch, tpm

Examples

# use Hessian = TRUE if you want standard errors
fit <- grm(Science[c(1,3,4,7)], Hessian = TRUE)
summary(fit)

## One factor model using the WIRS data;
## results are reported under the IRT
## parameterization
fit <- ltm(WIRS ~ z1)
summary(fit)