| monthglm | R Documentation | 
Fit a generalized linear model with a categorical variable of month.
monthglm(
  formula,
  data,
  family = gaussian(),
  refmonth = 1,
  monthvar = "month",
  offsetmonth = FALSE,
  offsetpop = NULL
)
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.  | 
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@qut.edu.au
Barnett, A.G., Dobson, A.J. (2010) Analysing Seasonal Health Data. Springer.
summary.monthglm, plot.monthglm
data(CVD)
mmodel = monthglm(formula=cvd~1 ,data=CVD, family=poisson(),
                  offsetpop=expression(pop/100000), offsetmonth=TRUE)
summary(mmodel)
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