I have a dataset that I exported from SQL that has the following format:
> head(my_data)
# A tibble: 6 x 19
referencedate var1 var2 cases var3 var4 var5
<dttm> <dbl> <dbl> <dbl> <chr> <dbl> <dbl>
1 2008-03-31 00:00:00 1 1 1 255124~ -1 -1
2 2008-03-31 00:00:00 1 1 3 441344~ -1 -1
3 2008-03-31 00:00:00 1 1 5 133497~ 1 0
4 2008-03-31 00:00:00 1 1 7 343242~ 1 -1
5 2008-03-31 00:00:00 1 1 100 292297~ 1 -1
6 2008-03-31 00:00:00 1 1 1 159941~ -1 0
If I run a logistic regression, the software thinks that each row is one observation, while depending on the value of cases there are multiple observations with the same values. How can I incorporate this in my analysis? This could be done by either generating multiple rows for when cases > 1, or with some other way...?