The`and` rule checks whether two activities both occur in a case (or are both absent). If activity A exists, Activity B should also exist, and vice versa.
and(activity_a, activity_b)
| activity_a | Activity A. A character vector of length one. This should be an activity of the event log supplied to `check_rule`. |
|---|---|
| activity_b | Activity B. A character vector of length one. This should be an activity of the event log supplied to `check_rule`. |
Other Declarative Rules: absent,
contains_between,
contains_exactly, contains,
ends, precedence,
responded_existence,
response, starts,
succession, xor
library(bupaR) library(eventdataR) # Check that if a patients is registered, he's also checked-out, and vice versa. patients %>% check_rule(and("Registration","Check-out"))#> Log of 5442 events consisting of: #> 7 traces #> 500 cases #> 2721 instances of 7 activities #> 7 resources #> Events occurred from 2017-01-02 11:41:53 until 2018-05-05 07:16:02 #> #> Variables were mapped as follows: #> Case identifier: patient #> Activity identifier: handling #> Resource identifier: employee #> Activity instance identifier: handling_id #> Timestamp: time #> Lifecycle transition: registration_type #> #> # A tibble: 5,442 x 8 #> handling patient employee handling_id registration_ty~ time #> <fct> <chr> <fct> <chr> <fct> <dttm> #> 1 Registr~ 1 r1 1 start 2017-01-02 11:41:53 #> 2 Registr~ 2 r1 2 start 2017-01-02 11:41:53 #> 3 Registr~ 3 r1 3 start 2017-01-04 01:34:05 #> 4 Registr~ 4 r1 4 start 2017-01-04 01:34:04 #> 5 Registr~ 5 r1 5 start 2017-01-04 16:07:47 #> 6 Registr~ 6 r1 6 start 2017-01-04 16:07:47 #> 7 Registr~ 7 r1 7 start 2017-01-05 04:56:11 #> 8 Registr~ 8 r1 8 start 2017-01-05 04:56:11 #> 9 Registr~ 9 r1 9 start 2017-01-06 05:58:54 #> 10 Registr~ 10 r1 10 start 2017-01-06 05:58:54 #> # ... with 5,432 more rows, and 2 more variables: .order <int>, #> # and_Registration_Check_out <lgl>