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 logtransform the offset as the logtransform 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 righthand side of
formula
.
This model is useful for examining nonsinusoidal 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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