getRates {diseasemapping} | R Documentation |
The getRates function calculates the estimated coefficient of the age and sex group from the case and population data set. It fits a glm model with Poisson distribution by default.
getRates(casedata, popdata, formula, family = 'poisson', minimumAge = 0, maximumAge = 100, S = c("M", "F"), years = NULL, year.range = NULL, case.years = grep("^year$", names(casedata), ignore.case = TRUE, value = TRUE), fit.numeric=NULL, breaks = NULL)
casedata |
A data frame of case data, with columns corresponding to variables in |
popdata |
population data set |
formula |
the glm model you want to fit. ie. |
family |
the distribution to fit the model |
minimumAge |
the lower boundary of the age, default is 0 |
maximumAge |
the higher boundary of the age, default is 100 |
S |
vector of sexes to include in the analysis. Defaults to both "M" and "F" |
years |
a vector of census years |
year.range |
study period: a vector of two elements, starting dates and ending dates |
case.years |
variable name in the case data which contains time |
fit.numeric |
the variables which needed to be changed from factor to numeric |
breaks |
the age breaks |
It fits a glm model with Poisson or binomial distribution over case and population data sets. If there is no data set in some age and sex group, an NA will show there.
A summary of the glm model contains set of estimated coefficients for different age and sex groups.
Patrick Brown
data('casedata') data('popdata') therates = getRates(casedata, popdata, ~sex*age, breaks=c(seq(0, 80, by=10), Inf)) therates