Plots the self controlled case series results for one analysis

Creates nice self controlled case series plots

Usage

plotSccsEstimates(
  sccsData,
  sccsDiagnostics = NULL,
  sccsMeta = NULL,
  includeCounts = TRUE,
  selectedAnalysisId
)

Arguments

sccsData

The self controlled case series data

sccsDiagnostics

(optional) The self controlled case series diagnostic data

sccsMeta

(optional) The self controlled case series evidence synthesis data

includeCounts

Whether to include count on the plot

selectedAnalysisId

The analysis ID of interest to plot

Value

Returns a ggplot with the estimates

Details

Input the self controlled case series data

See also

Other Estimation: .getCmVersion(), .getSccsVersion(), getCMEstimation(), getCmDiagnosticsData(), getCmMetaEstimation(), getCmNegativeControlEstimates(), getCmOutcomes(), getCmPropensityModel(), getCmTable(), getCmTargets(), getSccsDiagnosticsData(), getSccsEstimation(), getSccsMetaEstimation(), getSccsModel(), getSccsNegativeControlEstimates(), getSccsOutcomes(), getSccsTable(), getSccsTargets(), getSccsTimeToEvent(), plotCmEstimates()

Examples

conDet <- getExampleConnectionDetails()

connectionHandler <- ResultModelManager::ConnectionHandler$new(conDet)
#> Connecting using SQLite driver

sccsEst <- getSccsEstimation(
  connectionHandler = connectionHandler, 
  schema = 'main',
  targetIds = 1,
  outcomeIds = 3
)
plotSccsEstimates(
  sccsData = sccsEst, 
  sccsMeta = NULL, 
  selectedAnalysisId = 1
)
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> refline_col will be deprecated, use refline_gp instead.
#> footnote_col will be deprecated, use footnote_gp instead.
#> Warning: Missing lower and/or upper limit on column2 row 3
#> $`Celecoxib-GI bleed-NA`

#>