Description Usage Arguments Details Value Note Author(s) References See Also Examples

Computes linear transformation constants to equate a set of GRM/GPCM item parameters to a target scale using a test characteristic curve equating procedure (Stocking & Lord, 1983)

1 2 |

`ipar.to` |
a data frame containing target item parameters in the following order: a, cb1, cb2,..., cb(maxCat-1) |

`ipar.from` |
a data frame containing to-be-equated item parameters in the following order: a, cb1, cb2,..., cb(maxCat-1) |

`theta` |
a theta grid |

`model` |
IRT model, either "GRM" or "GPCM" |

`start.AK` |
a vector of starting values, c(A, K) where A is a multiplicative constant and K is an additive constant |

`lower.AK` |
a vector of lower limits, c(A, K) where A is a multiplicative constant and K is an additive constant |

`upper.AK` |
a vector of upper limits, c(A, K) where A is a multiplicative constant and K is an additive constant |

Computes linear transformation constants (A and K) that equate a set of item parameters (ipar.from) to the scale defined by a target item parameters (ipar.to) by minimizing the squared difference between the test characteristic curves (Stocking & Lord, 1983). The minimization is performed by the nlminb function (in stats).

returns a vector of two elements, c(A, K) where A is a multiplicative constant and K is an additive constant

The item parameters are assumed to be on the theta metric (0,1). The number of category threshold parameters may differ across items but not greater than (maxCat-1).

Seung W. Choi <[email protected]>

Stocking, M. L. & Lord, F. M. (1983). Developing a Common Metric in Item Response Theory. Applied Psychological Measurement, 7(2), 201-210.

1 2 3 4 5 | ```
##ipar.to is a data frame containing "target" item parameters
##ipar.from is a data frame containing "to-be-equated" item parameters
## Not run: AK <- equate(ipar.to,ipar.from)
#AK[1] contains the multiplicative constant
#AK[2] contains the additive constant
``` |

```
Loading required package: mirt
Loading required package: stats4
Loading required package: lattice
Loading required package: rms
Loading required package: Hmisc
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2
Attaching package: 'Hmisc'
The following objects are masked from 'package:base':
format.pval, units
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
```

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