Plot prevalence results

Plot prevalence results

Usage

plotPrevalence(
  result,
  x = "prevalence_start_date",
  y = "prevalence",
  line = FALSE,
  point = TRUE,
  ribbon = FALSE,
  ymin = "prevalence_95CI_lower",
  ymax = "prevalence_95CI_upper",
  facet = NULL,
  colour = NULL
)

Arguments

result

Prevalence results

x

Variable to plot on x axis

y

Variable to plot on y axis.

line

Whether to plot a line using geom_line

point

Whether to plot points using geom_point

ribbon

Whether to plot a ribbon using geom_ribbon

ymin

Lower limit of error bars, if provided is plot using geom_errorbar

ymax

Upper limit of error bars, if provided is plot using geom_errorbar

facet

Variables to use for facets. To see available variables for facetting use the function availablePrevalenceGrouping().

colour

Variables to use for colours. To see available variables for colouring use the function availablePrevalenceGrouping().

Value

A ggplot with the prevalence results plotted

Examples

# \donttest{
cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2014-01-01"), as.Date("2018-01-01"))
)
#> ℹ Creating denominator cohorts
#> ! cohort columns will be reordered to match the expected order:
#>   cohort_definition_id, subject_id, cohort_start_date, and cohort_end_date.
#> ✔ Cohorts created in 0 min and 2 sec
prev <- estimatePointPrevalence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome"
)
#> ℹ Getting prevalence for analysis 1 of 1
#> ✔ Time taken: 0 mins and 0 secs
plotPrevalence(prev)

# }