Description Usage Arguments Value Author(s) See Also Examples

Estimates a logistic regression model by maximizing the conditional likelihood. The conditional likelihood calculations are exact, and scale efficiently to strata with large numbers of cases.

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`formula` |
Model formula |

`strata` |
Factor describing membership of strata for conditioning |

`data` |
data frame containing the variables in the formula and strata arguments |

`subset` |
subset of records to use |

`na.action` |
missing value handling |

`init` |
initial values |

`model` |
a logical value indicating whether |

`x,y` |
logical values indicating whether the response vector and model matrix used in the fitting process should be returned as components of the returned value. |

`contrasts` |
an optional list. See the |

`iter.max` |
maximum number of iterations |

`eps` |
Convergence tolerance. Iteration continues until the relative
change in the conditional log likelihood is less than |

`toler.chol` |
Tolerance used for detection of a singularity during a Cholesky
decomposition of the variance matrix. This is used to detect
redundant predictor variables. Must be less than |

An object of class `"clogistic"`

. This is a list containing
the following components:

`coefficients` |
the estimates of the log-odds ratio parameters. If the model is over-determined there will be missing values in the vector corresponding to the redundant columns in the model matrix. |

`var` |
the variance matrix of the coefficients. Rows and columns corresponding to any missing coefficients are set to zero. |

`loglik` |
a vector of length 2 containing the log-likelihood with the initial values and with the final values of the coefficients. |

`iter` |
number of iterations used. |

`n` |
number of observations used. Observations may be dropped
either because they are missing, or because they belong to a
homogeneous stratum. For more details on which observations were
used, see |

`informative` |
if |

The output will also contain the following, for documentation see the
`glm`

object: `terms`

, `formula`

,
`call`

, `contrasts`

, `xlevels`

, and, optionally,
`x`

, `y`

, and/or `frame`

.

Martyn Plummer

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