Description Usage Arguments Details Value Author(s) References See Also Examples

Fit a generalized linear model with a categorical variable of month.

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`formula` |
regression model formula, e.g., |

`data` |
a data frame. |

`family` |
a description of the error distribution and link
function to be used in the model (default= |

`refmonth` |
reference month, must be between 1 and 12 (default=1 for January). |

`monthvar` |
name of the month variable which is either an integer (1 to 12) or a character or factor (‘Jan’ to ‘Dec’ or ‘January’ to ‘December’) (default='month'). |

`offsetmonth` |
include an offset to account for the uneven number
of days in the month (TRUE/FALSE). Should be used for monthly counts
(with |

`offsetpop` |
include an offset for the population (optional), this should be a variable in the data frame. Do not log-transform the offset as the log-transform is applied by the function. |

`x` |
Object of class |

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

Month is fitted as a categorical variable as part of a
generalized linear model. Other independent variables can be added to
the right-hand side of `formula`

.

This model is useful for examining non-sinusoidal seasonal
patterns. For sinusoidal seasonal patterns see `cosinor`

.

The data frame should contain the integer months and the year as a 4 digit number. These are used to calculate the number of days in each month accounting for leap years.

`call` |
the original call to the monthglm function. |

`fit` |
GLM model. |

`fitted` |
fitted values. |

`residuals` |
residuals. |

`out` |
details on the monthly estimates. |

Adrian Barnett a.barnett<at>qut.edu.au

Barnett, A.G., Dobson, A.J. (2010) *Analysing Seasonal Health Data*. Springer.

`summary.monthglm`

, `plot.monthglm`

1 2 3 4 |

```
Loading required package: ggplot2
Loading required package: MASS
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-20. For overview type 'help("mgcv-package")'.
Loading required package: survival
Loading required package: coda
Number of observations = 168
Rate ratios
mean lower upper zvalue pvalue
monthsFeb 0.9001334 0.8835557 0.9170223 -11.093389 1.350710e-28
monthsMar 0.8248895 0.8097153 0.8403480 -20.321628 8.278563e-92
monthsApr 0.7861180 0.7713300 0.8011895 -24.836563 3.612571e-136
monthsMay 0.7431550 0.7290823 0.7574993 -30.432988 2.011735e-203
monthsJun 0.7169580 0.7031100 0.7310788 -33.437125 3.960379e-245
monthsJul 0.7001582 0.6866705 0.7139109 -35.915811 1.730663e-282
monthsAug 0.7037277 0.6901913 0.7175297 -35.456352 2.315335e-275
monthsSep 0.7033356 0.6896741 0.7172678 -35.164379 7.008762e-271
monthsOct 0.7365838 0.7226003 0.7508379 -31.263630 1.457403e-214
monthsNov 0.7894712 0.7746378 0.8045886 -24.426747 8.891612e-132
monthsDec 0.9286091 0.9120533 0.9454655 -8.069682 7.048164e-16
```

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