Compute several person-fit statistics.

1 2 3 4 |

`matrix` |
Data matrix of dichotomous item scores: Persons as rows, items as columns, item scores are either 0 or 1, missing values allowed. |

`method` |
Vector of person-fit statistics to be computed. |

`simplified` |
Logical. If FALSE, a list of |

`NA.method` |
Method to deal with missing values. The default is pairwise elimination ( |

`Save.MatImp` |
Logical. Save (imputted) data matrix to file? Default is FALSE. |

`IP` |
Matrix with previously estimated item parameters: One row per item, and three columns ([,1] item discrimination; [,2] item difficulty; [,3] lower-asymptote, also referred to as pseudo-guessing parameter). In case no item parameters are available then |

`IRT.PModel` |
Specify the IRT model to use in order to estimate the item parameters (only if |

`Ability` |
Vector with previoulsy estimated latent ability parameters, one per respondent, following the order of the row index of In case no ability parameters are available then |

`Ability.PModel` |
Specify the method to use in order to estimate the latent ability parameters (only if |

`mu` |
Mean of the apriori distribution. Only used when |

`sigma` |
Standard deviation of the apriori distribution. Only used when |

Function `PerFit.PFS`

is a wrapper allowing to compute more than one person-fit statistic simultaneously.

If `simplified=TRUE`

, a N-by-m data frame is returned, where N is the number of respondents and m is the number of methods.

If `simplified=FALSE`

a list of m `PerFit`

objects is returned.

Jorge N. Tendeiro j.n.tendeiro@rug.nl

1 2 3 4 5 | ```
# Load the inadequacy scale data (dichotomous item scores):
data(InadequacyData)
# Compute the lzstar, U3, and Ht scores:
PerFit.PFS(InadequacyData, method=c("lzstar", "U3", "Ht"))
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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