summary.glm {stats} | R Documentation |

These functions are all `methods`

for class `glm`

or
`summary.glm`

objects.

## S3 method for class 'glm': summary(object, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...) ## S3 method for class 'summary.glm': print(x, digits = max(3, getOption("digits") - 3), symbolic.cor = x$symbolic.cor, signif.stars = getOption("show.signif.stars"), ...)

`object` |
an object of class `"glm"` , usually, a result of a
call to `glm` . |

`x` |
an object of class `"summary.glm"` , usually, a result of a
call to `summary.glm` . |

`dispersion` |
the dispersion parameter for the fitting family.
By default it is obtained from `object` . |

`correlation` |
logical; if `TRUE` , the correlation matrix of
the estimated parameters is returned and printed. |

`digits` |
the number of significant digits to use when printing. |

`symbolic.cor` |
logical. If `TRUE` , print the correlations in
a symbolic form (see `symnum` ) rather than as numbers. |

`signif.stars` |
logical. If `TRUE` , “significance stars”
are printed for each coefficient. |

`...` |
further arguments passed to or from other methods. |

`print.summary.glm`

tries to be smart about formatting the
coefficients, standard errors, etc. and additionally gives
“significance stars” if `signif.stars`

is `TRUE`

.

Aliased coefficients are omitted in the returned object but (as from **R**
1.8.0) restored by the `print`

method.

Correlations are printed to two decimal places (or symbolically): to
see the actual correlations print `summary(object)$correlation`

directly.

The dispersion is taken as `1`

in the `binomial`

and
`Poisson`

families, and otherwise estimated by the residual
Chisquared statistic divided by the residual degrees of freedom.

`summary.glm`

returns an object of class `"summary.glm"`

, a
list with components

`call` |
the component from `object` . |

`family` |
the component from `object` . |

`deviance` |
the component from `object` . |

`contrasts` |
the component from `object` . |

`df.residual` |
the component from `object` . |

`null.deviance` |
the component from `object` . |

`df.null` |
the component from `object` . |

`deviance.resid` |
the deviance residuals:
see `residuals.glm` . |

`coefficients` |
the matrix of coefficients, standard errors, z-values and p-values. Aliased coefficients are omitted. |

`aliased` |
named logical vector showing if the original coefficients are aliased. |

`dispersion` |
either the supplied argument or the estimated
dispersion if the latter is `NULL` |

`df` |
a 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of non-aliased coefficients. |

`cov.unscaled` |
the unscaled (`dispersion = 1` ) estimated covariance
matrix of the estimated coefficients. |

`cov.scaled` |
ditto, scaled by `dispersion` . |

`correlation` |
(only if `correlation` is true.) The estimated
correlations of the estimated coefficients. |

`symbolic.cor` |
(only if `correlation` is true.) The value
of the argument `symbolic.cor` . |

## --- Continuing the Example from '?glm': summary(glm.D93)

[Package *stats* version 2.2.1 Index]