# guesspar

##### Extract Guessing Parameters of Item Response Models

A class and generic function for representing and extracting the so-called guessing parameters of a given item response model.

- Keywords
- classes

##### Usage

```
guesspar(object, …)
# S3 method for raschmodel
guesspar(object, alias = TRUE, vcov = TRUE, …)
# S3 method for rsmodel
guesspar(object, alias = TRUE, vcov = TRUE, …)
# S3 method for pcmodel
guesspar(object, alias = TRUE, vcov = TRUE, …)
# S3 method for plmodel
guesspar(object, alias = TRUE, logit = FALSE, vcov = TRUE, …)
# S3 method for gpcmodel
guesspar(object, alias = TRUE, vcov = TRUE, …)
```

##### Arguments

- object
a fitted model object whose guessing parameters should be extracted.

- alias
logical. If

`TRUE`

(the default), the aliased parameters are included in the return vector (and in the variance-covariance matrix if`vcov`

= TRUE). If`FALSE`

, these parameters are removed. For`raschmodel`

s,`rsmodel`

s,`pcmodel`

s and`gpcmodel`

s, where all guessing parameters are fixed to 0, this means that an empty numeric vector and an empty variance-covariace matrix is returned if`alias`

is`FALSE`

.- logit
logical. If a

`plmodel`

of`type`

`"3PL"`

or`"4PL"`

model has been fit, the guessing parameters were estimated on the logit scale. If`logit = FALSE`

, these estimates and the variance-covariance (if requested) are retransformed using the logistic function and the delta method.- vcov
logical. If

`TRUE`

(the default), the variance-covariance matrix of the guessing parameters is attached as attribute`vcov`

.- …
further arguments which are currently not used.

##### Details

`guesspar`

is both, a class to represent guessing parameters of item
response models as well as a generic function. The generic function can be
used to extract the guessing parameters of a given item response model.

For objects of class `guesspar`

, several methods to standard generic
functions exist: `print`

, `coef`

, `vcov`

. `coef`

and
`vcov`

can be used to extract the guessing parameters and their
variance-covariance matrix without additional attributes.

##### Value

A named vector with guessing parameters of class `guesspar`

and
additional attributes `model`

(the model name), `alias`

(either
`TRUE`

or a named numeric vector with the aliased parameters not included
in the return value), `logit`

(indicating whether the estimates are on the
logit scale or not), and `vcov`

(the estimated and adjusted
variance-covariance matrix).

##### See Also

##### Examples

```
# NOT RUN {
if(requireNamespace("mirt")) {
o <- options(digits = 3)
## load simulated data
data("Sim3PL", package = "psychotools")
## fit 2PL to data simulated under the 3PL
twoplmod <- plmodel(Sim3PL$resp)
## extract the guessing parameters (all fixed at 0)
gp1 <- guesspar(twoplmod)
## fit 3PL to data simulated under the 3PL
threeplmod <- plmodel(Sim3PL$resp, type = "3PL")
## extract the guessing parameters
gp2 <- guesspar(threeplmod)
## extract the standard errors
sqrt(diag(vcov(gp2)))
## extract the guessing parameters on the logit scale
gp2_logit <- guesspar(threeplmod, logit = TRUE)
## along with the delta transformed standard errors
sqrt(diag(vcov(gp2_logit)))
options(digits = o$digits)
}
# }
```

*Documentation reproduced from package psychotools, version 0.5-1, License: GPL-2 | GPL-3*