Fit a GLM with Month

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

Usage

monthglm(
  formula,
  data,
  family = stats::gaussian(),
  refmonth = 1,
  monthvar = "month",
  offsetmonth = FALSE,
  offsetpop = NULL
)

Arguments

formula: regression model formula, e.g., y~x1+x2, (do not add month to the regression equation, it will be added automatically).
data: a data frame. Must contain the column "months" as integer, and year as a 4 digit number.
family: a description of the error distribution and link function to be used in the model (default=gaussian()). (See family() for details of family functions.).
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 family=poisson()).
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. This should be an expression, as given in the example below.

Value

a list with the following elements:

call: the original call to the monthglm function.
fit: GLM model.
fitted: fitted values.
residuals: residuals.
out: details on the monthly estimates.

Details

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.

References

Barnett, A.G., Dobson, A.J. (2010) Analysing Seasonal Health Data. Springer. doi:10.1007/978-3-642-10748-1

Author

Adrian Barnett a.barnett@qut.edu.au

Examples


model <- monthglm(
  formula = cvd~1,
  data = CVD,
  family = poisson(),
  offsetpop = expression(pop/100000),
  offsetmonth = TRUE
  )
summary(model)
#> 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