This package provides functions to create an incidence or prevalence
plot. There are a couple of options that can be specified when creating
such a plot. In this vignette we are using the options in the
plotIncidence
function, however these same options can be
specified in the plotPrevalence
function.
cdm <- mockIncidencePrevalenceRef(
sampleSize = 10000,
outPre = 0.5
)
#> Warning: ! 17 column in person do not match expected column type:
#> • `person_id` is character but expected integer
#> • `gender_concept_id` is character but expected integer
#> • `year_of_birth` is numeric but expected integer
#> • `month_of_birth` is numeric but expected integer
#> • `day_of_birth` is numeric but expected integer
#> • `race_concept_id` is logical but expected integer
#> • `ethnicity_concept_id` is logical but expected integer
#> • `location_id` is character but expected integer
#> • `provider_id` is character but expected integer
#> • `care_site_id` is character but expected integer
#> • `person_source_value` is integer but expected character
#> • `gender_source_value` is integer but expected character
#> • `gender_source_concept_id` is character but expected integer
#> • `race_source_value` is integer but expected character
#> • `race_source_concept_id` is character but expected integer
#> • `ethnicity_source_value` is integer but expected character
#> • `ethnicity_source_concept_id` is character but expected integer
#> Warning: ! 3 column in observation_period do not match expected column type:
#> • `observation_period_id` is character but expected integer
#> • `person_id` is character but expected integer
#> • `period_type_concept_id` is logical but expected integer
#> Warning in validateCdmReference(cdm, soft = .softValidation): There are observation period end dates after the current date: 2024-09-30
#> ℹ The latest max observation period end date found is 2089-06-28
#> Warning: ! 1 column in target do not match expected column type:
#> • `subject_id` is character but expected integer
#> Warning: ! 1 column in outcome do not match expected column type:
#> • `subject_id` is character but expected integer
#> Warning: ! 17 column in person do not match expected column type:
#> • `person_id` is character but expected integer
#> • `gender_concept_id` is character but expected integer
#> • `year_of_birth` is numeric but expected integer
#> • `month_of_birth` is numeric but expected integer
#> • `day_of_birth` is numeric but expected integer
#> • `race_concept_id` is logical but expected integer
#> • `ethnicity_concept_id` is logical but expected integer
#> • `location_id` is character but expected integer
#> • `provider_id` is character but expected integer
#> • `care_site_id` is character but expected integer
#> • `person_source_value` is integer but expected character
#> • `gender_source_value` is integer but expected character
#> • `gender_source_concept_id` is character but expected integer
#> • `race_source_value` is integer but expected character
#> • `race_source_concept_id` is character but expected integer
#> • `ethnicity_source_value` is integer but expected character
#> • `ethnicity_source_concept_id` is character but expected integer
#> Warning: ! 3 column in observation_period do not match expected column type:
#> • `observation_period_id` is character but expected integer
#> • `person_id` is character but expected integer
#> • `period_type_concept_id` is logical but expected integer
#> Warning in validateCdmReference(cdm, soft = .softValidation): There are observation period end dates after the current date: 2024-09-30
#> ℹ The latest max observation period end date found is 2089-06-28
#> Warning: ! 1 column in target do not match expected column type:
#> • `subject_id` is character but expected integer
#> Warning: ! 1 column in outcome do not match expected column type:
#> • `subject_id` is character but expected integer
cdm <- generateDenominatorCohortSet(
cdm = cdm, name = "denominator",
cohortDateRange = c(as.Date("2008-01-01"), as.Date("2012-01-01")),
sex = c("Male", "Female")
)
#> ℹ Creating denominator cohorts
#> Warning: ! 5 casted column in denominator (cohort_attrition) as do not match expected
#> column type:
#> • `number_records` from numeric to integer
#> • `number_subjects` from numeric to integer
#> • `reason_id` from numeric to integer
#> • `excluded_records` from numeric to integer
#> • `excluded_subjects` from numeric to integer
#> Warning: ! 1 column in denominator do not match expected column type:
#> • `subject_id` is character but expected integer
#> ✔ Cohorts created in 0 min and 4 sec
inc <- estimateIncidence(
cdm = cdm,
denominatorTable = "denominator",
outcomeTable = "outcome",
interval = "years"
)
#> Getting incidence for analysis 1 of 2
#> Getting incidence for analysis 2 of 2
#> Overall time taken: 0 mins and 1 secs
This is the default incidence plot where the plot has been faceted by sex.
This is the previous plot where the dots are connected.
This is the previous plot where the dots are connected but no confidence interval is shown.
This is the previous plot where the subplots are shown on top of each
other. The facetNcols
variable defines the number of
columns of the subplots. In addition we set facetScales
as
“free” so that the axis can vary by facet.