Extracts the estimated parameters from either `grm`

, `ltm`

, `rasch`

or `tpm`

objects.

```
# S3 method for gpcm
coef(object, …)
```# S3 method for grm
coef(object, …)

# S3 method for ltm
coef(object, standardized = FALSE, prob = FALSE, order = FALSE, …)

# S3 method for rasch
coef(object, prob = FALSE, order = FALSE, …)

# S3 method for tpm
coef(object, prob = FALSE, order = FALSE, …)

object

an object inheriting from either class `gpcm`

, class `grm`

, class `ltm`

, class `rasch`

or class `tpm`

.

standardized

logical; if `TRUE`

the standardized loadings are also returned. See **Details**
for more info.

prob

logical; if `TRUE`

the probability of a positive response for the median individual
(i.e., \(Pr(x_i = 1 | z = 0)\), with \(i = 1, \ldots, p\) denoting the items)
is also returned.

order

logical; if `TRUE`

the items are sorted according to the difficulty estimates.

…

additional arguments; currently none is used.

A list or a matrix of the estimated parameters for the fitted model.

The standardization of the factor loadings is useful in order to form a link to the
Underlying Variable approach. In particular, the standardized form of the factor loadings
represents the correlation coefficient between the latent variables and the underlying continuous variables
based on which the dichotomous outcomes arise (see Bartholomew and Knott, 1999, p.87-88 or Bartholomew
*et al.*, 2002, p.191).

The standardized factor loadings are computed only for the linear one- and two-factor models, fitted by `ltm()`

.

Bartholomew, D. and Knott, M. (1999) *Latent Variable Models
and Factor Analysis*, 2nd ed. London: Arnold.

Bartholomew, D., Steel, F., Moustaki, I. and Galbraith, J. (2002)
*The Analysis and Interpretation of Multivariate Data for
Social Scientists*. London: Chapman and Hall.

```
# NOT RUN {
fit <- grm(Science[c(1,3,4,7)])
coef(fit)
fit <- ltm(LSAT ~ z1)
coef(fit, TRUE, TRUE)
m <- rasch(LSAT)
coef(fit, TRUE, TRUE)
# }
```

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