`raschmodel`

is a basic fitting function for simple Rasch models.

1 2 3 |

`y` |
object that can be coerced (via |

`weights` |
an optional vector of weights (interpreted as case weights). |

`start` |
an optional vector of starting values. |

`deriv` |
character. Which type of derivatives should be used for computing
gradient and Hessian matrix? Analytical with sum algorithm ( |

`hessian` |
logical. Should the Hessian of the final model be computed?
If set to |

`reltol, maxit, ...` |
further arguments passed to |

`full` |
logical. Should a full model object be returned? If set to |

`gradtol, iterlim` |
numeric. For backward compatibility with previous versions
these arguments are mapped to |

`raschmodel`

provides a basic fitting function for simple Rasch models,
intended as a building block for fitting Rasch trees and Rasch mixtures
in the psychotree and psychomix packages, respectively.

`raschmodel`

returns an object of class `"raschmodel"`

for which
several basic methods are available, including `print`

, `plot`

,
`summary`

, `coef`

, `vcov`

, `logLik`

, `estfun`

,
`discrpar`

, `itempar`

, `threshpar`

,
and `personpar`

.

`raschmodel`

returns an S3 object of class `"raschmodel"`

,
i.e., a list with the following components:

`coefficients` |
estimated item difficulty parameters (without first item parameter which is always constrained to be 0), |

`vcov` |
covariance matrix of the parameters in the model, |

`loglik` |
log-likelihood of the fitted model, |

`df` |
number of estimated parameters, |

`data` |
the original data supplied (excluding columns without variance), |

`weights` |
the weights used (if any), |

`n` |
number of observations (with non-zero weights), |

`items` |
status indicator (0, 0/1, 1) of all original items, |

`na` |
logical indicating whether the data contains NAs, |

`elementary_symmetric_functions` |
List of elementary symmetric functions for estimated parameters (up to order 2; or 1 in case of numeric derivatives), |

`code` |
convergence code from |

`iterations` |
number of iterations used by |

`reltol` |
tolerance passed to |

`deriv` |
type of derivatives used for computing gradient and Hessian matrix. |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
o <- options(digits = 4)
## Verbal aggression data
data("VerbalAggression", package = "psychotools")
## Rasch model for the other-to-blame situations
m <- raschmodel(VerbalAggression$resp2[, 1:12])
summary(m)
## visualizations
plot(m, type = "profile")
plot(m, type = "regions")
plot(m, type = "curves")
plot(m, type = "information")
plot(m, type = "piplot")
options(digits = o$digits)
``` |

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