Description Usage Arguments Details Author(s) See Also Examples

Plots characteristic curve of IRT model.

1 | ```
plotDIFirt(parameters, test = "Lord", item = "all", item.name, same.scale = F)
``` |

`parameters` |
numeric: data matrix or data frame. See |

`test` |
character: type of statistic to be shown. See |

`item` |
either character ("all"), or numeric vector, or single number
corresponding to column indicators. See |

`item.name` |
character: the name of item. |

`same.scale` |
logical: are the item |

This function plots characteristic curve of DIF IRT model.

The `parameters`

matrix has a number of rows equal to twice the number
of items in the data set. The first J rows refer to the item parameter estimates
in the reference group, while the last J ones correspond to the same items in the
focal group. The number of columns depends on the selected IRT model: 2 for the 1PL
model, 5 for the 2PL model, 6 for the constrained 3PL model and 9 for the
unconstrained 3PL model. The columns of irtParam have to follow the same structure
as the output of `itemParEst`

, `difLord`

or `difRaju`

command from
`difR`

package.

Two possible type of `test`

statistics can be visualized - `"Lord"`

gives only characteristic curves, `"Raju"`

also highlights area between
these curves.

For default option `"all"`

, all characteristic curves are plotted.

Adela Drabinova

Institute of Computer Science, The Czech Academy of Sciences

Faculty of Mathematics and Physics, Charles University

[email protected]

Patricia Martinkova

Institute of Computer Science, The Czech Academy of Sciences

[email protected]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
## Not run:
# loading libraries
library(difR)
library(ltm)
# loading data based on GMAT2
data(GMAT2, package = "difNLR")
# Estimation of 2PL IRT model and Lord's statistic
# by difR package
fitLord <- difLord(GMAT2, group = 21, focal.name = 1, model = "2PL")
# plot of item 1 and Lord's statistic
plotDIFirt(fitLord$itemParInit, item = 1)
# Estimation of 2PL IRT model and Raju's statistic
# by difR package
fitRaju <- difRaju(GMAT2, group = 21, focal.name = 1, model = "2PL")
# plot of item 1 and Lord's statistic
plotDIFirt(fitRaju$itemParInit, test = "Raju", item = 1)
## End(Not run)
``` |

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