Modules are groups, to which steps can be assigned, e.g., you might assign all steps, in which the immune system is involved, to module “immune system”. With modules, it is easier to see if certain groups are involved in sufficient causes, e.g., if there are sufficient causes without any involvement of the immune system.
Define modules
Modules are defined during steplist creation. You don’t have to use
modules, but if you do, every step has to be part of exactly one module.
During steplist checking, it leads to an error if only some steps have
been assigned a module. For quick removal of all modules, use
remove_all_modules()
. Once the SCC model has been created,
the information, if modules are used or not, is saved in element
sc_use_modules
of epicmodel_scc
class
objects.
Plot steplist
After successful checking, steplists can be plotted to see all steps
chained together. By default, if modules have been used, nodes in the
graph are colored according to their module with all steps in the same
module having the same color. Use arguments modules
and
module_colors
to turn coloring off and change colors,
respectively.
Mechanisms
Since mechanisms and steplist plotting works similarly,
mechanism()
offers arguments modules
and
module_colors
as well and they work similarly to
plot.epicmodel_steplist_checked()
.
SCC model summary
When printing a SCC model that uses modules, the output also reports
how many steps in the sufficient cause-specific mechanism belong to each
module. Let’s look at the built-in steplist_party
as an
example. First, we load the steplist, make some adjustments that would
cause steplist checking to fail, and finally run
check_steplist()
. Next, we create the SCC model from the
checked steplist and print the model.
steplist_checked <- steplist_party %>% remove_na() %>% remove_segment("d4") %>% check_steplist()
scc_model <- steplist_checked %>% create_scc()
scc_model
#>
#> ── Outcome Definitions ──
#>
#> • Emma is coming and food is fine and Laura is coming and weather is fine
#>
#> ── SC 1 ──
#>
#> ✔ Always sufficient
#> Component causes:
#> • Emma is invited
#> • Laura is invited
#> • Birthday party takes place on a weekday
#> • Birthday party takes place at a karaoke bar
#>
#> Modules
#> • guests: 40% (4/10)
#> • orga: 40% (4/10)
#> • food: 20% (2/10)
#>
#> ── SC 2 ──
#>
#> ✔ Always sufficient
#> Component causes:
#> • Ana is invited
#> • Emma is invited
#> • Laura is invited
#> • Birthday party takes place at a restaurant
#>
#> Modules
#> • guests: 60% (6/10)
#> • orga: 30% (3/10)
#> • food: 10% (1/10)
#>
#> ── SC 3 ──
#>
#> ! Sufficiency depends on order of occurrence
#> Component causes:
#> • Ana is invited
#> • Emma is invited
#> • Laura is invited
#> • Birthday party takes place on a weekday
#> • No rain
#> • Birthday party takes place at the beach
#>
#> Sufficient orders of occurrence:
#> • Ana is invited -> birthday party takes place on a weekday
#>
#> Modules
#> • guests: 46% (6/13)
#> • orga: 38% (5/13)
#> • food: 15% (2/13)
#>
From the output, we can see that, e.g., sufficient cause 1 (SC 1) includes 10 steps in its minimally sufficient mechanism from component causes to the outcome of interest, of which 4 have been assigned to module “guests”, 4 have been assigned to module “orga”, and 2 have been assigned to module “food”.