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new articletidy-dev-day 🤓Tidyverse Developer Day rstd.io/tidy-dev-dayTidyverse Developer Day rstd.io/tidy-dev-day
Description
With the new tidymodels offsets package (offsetreg), I realize that we have not documented that this can already be done:
library(tidymodels)
library(offsetreg)
library(poissonreg)
us_deaths$offset <- log(us_deaths$population)
fit <-
poisson_reg() %>%
fit(deaths ~ gender + age_group + year + offset(offset), data = us_deaths)
tidy(fit)
#> # A tibble: 9 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) -18.3 0.136 -135. 0
#> 2 genderMale 0.328 0.000388 845. 0
#> 3 age_group35-44 0.443 0.00177 250. 0
#> 4 age_group45-54 1.21 0.00155 780. 0
#> 5 age_group55-64 1.99 0.00146 1367. 0
#> 6 age_group65-74 2.71 0.00143 1899. 0
#> 7 age_group75-84 3.65 0.00141 2579. 0
#> 8 age_group85+ 4.77 0.00140 3402. 0
#> 9 year 0.00568 0.0000672 84.5 0```
<sup>Created on 2024-01-23 with [reprex v2.0.2](https://reprex.tidyverse.org)</sup>Metadata
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new articletidy-dev-day 🤓Tidyverse Developer Day rstd.io/tidy-dev-dayTidyverse Developer Day rstd.io/tidy-dev-day