Description Usage Arguments Details Value Examples
For each exposure the dataset is copied and the original value replaced by the reference value. Then the sim function is used to generate 500 simulations of expected responses for each row. Finally the dataset is transformed to obtain expected response for original and reference values of the given exposures for each original row of the dataset.
1  est_attrib(fit, data, exposures, n_sim = 500)

fit 
A model fit constructed by fit_attrib 
data 
The observed data 
exposures 
The exposures that will get reference expected mortalities 
n_sim 
Number of simulations For more details see the help vignette:

The burden method is based on Nielsen, Krause, Molbak <doi:10.1111/irv.12564>.
For more details see the help vignette:
vignette("intro", package="attrib")
Dataset with expected responses for all simulations including expected responses given the exposure reference values
1 2 3 4 5 6 7 8 9 10 11 12  response < "deaths"
fixef < "pr100_ili_lag_1 + sin(2 * pi * (week  1) / 52) + cos(2 * pi * (week  1) / 52)"
ranef < " (pr100_ili_lag_1 season)"
offset < "log(pop)"
data < attrib::data_fake_nation
fit < fit_attrib(data = data, response = response, fixef = fixef, ranef = ranef, offset = offset)
exposures < c(pr100_ili_lag_1 = 0)
n_sim < 5
new_data < est_attrib(fit, data, exposures, n_sim)
new_data[]

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