cirtmodel {airt} | R Documentation |

## Fits a continuous IRT model.

### Description

This function fits a continuous Item Response Theory (IRT) model to the algorithm performance data. The function EstCRMitem in the R package EstCRM is updated to accommodate negative discrimination.

### Usage

```
cirtmodel(df, max.item = NULL, min.item = NULL)
```

### Arguments

`df` |
The performance data in a matrix or dataframe. |

`max.item` |
A vector with the maximum performance value for each algorithm. |

`min.item` |
A vector with the minimum performance value for each algorithm. |

### Value

A list with the following components:

`model` |
The IRT model. |

`anomalous` |
A binary value for each algorithm. It is set to 1 if an algorithm is anomalous. Otherwise it is set to 0. |

`consistency` |
The consistency of each algorithm. |

`difficulty_limit` |
The difficulty limit of each algorithm. A higher difficulty limit indicates that the algorithm can tackle harder problems. |

### References

Zopluoglu C (2022). EstCRM: Calibrating Parameters for the Samejima's Continuous IRT Model. R package version 1.6, https://CRAN.R-project.org/package=EstCRM.

### Examples

```
set.seed(1)
x1 <- runif(100)
x2 <- runif(100)
x3 <- runif(100)
X <- cbind.data.frame(x1, x2, x3)
mod <- cirtmodel(X)
```

*airt*version 0.2.2 Index]