Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
warning = FALSE,
message = FALSE
)
## ----thresholds---------------------------------------------------------------
library(SelfControlledCohort)
str(getDefaultDiagnosticThresholds())
## ----eval=FALSE---------------------------------------------------------------
# # Well-powered study
# computeMdrrForRateRatio(
# exposedPersonTime = 50000,
# unexposedPersonTime = 150000,
# exposedEvents = 40,
# unexposedEvents = 90
# )
#
# # Underpowered study (SRL1 solver returns NA if power cannot be met)
# computeMdrrForRateRatio(
# exposedPersonTime = 500,
# unexposedPersonTime = 1500,
# exposedEvents = 3,
# unexposedEvents = 7
# )
## ----eval=FALSE---------------------------------------------------------------
# # Compute EASE from negative control estimates
# negatives <- data.frame(
# rr = c(1.2, 0.8, 1.0, 1.1, 0.95),
# seLogRr = c(0.2, 0.1, 0.3, 0.15, 0.25)
# )
# computeEase(negatives)
## ----eval=FALSE---------------------------------------------------------------
# thresholds <- getDefaultDiagnosticThresholds()
# thresholds$mdrrMaxAcceptable <- 15.0 # Allow higher MDRR
# thresholds$maxPreExposureProportion <- 0.10 # Allow up to 10% pre-exposure
#
# runSelfControlledCohort(
# ...,
# runDiagnostics = TRUE,
# diagnosticThresholds = thresholds
# )
## ----eval=FALSE---------------------------------------------------------------
# diagnostics <- read.csv("results/scc_diagnostics_summary.csv")
#
# # Which target-outcome pairs had failures?
# failures <- diagnostics[diagnostics$pass == 0 &
# !(diagnostics$diagnostic_name %in% c("UNBLIND", "UNBLIND_FOR_CALIBRATION")), ]
# print(failures)
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