Standardized Incidence / Mortality Ratio (SIR / SMR) — standardizedratio • ClinicoPath

Computes standardized incidence ratios (SIR) or standardized mortality ratios (SMR) by indirect standardization. For each stratum the number of expected events is obtained by applying reference-population rates to the observed person-time; the SIR/SMR is the ratio of total observed to total expected events. Exact Poisson confidence intervals and a test against the null value of 1 are provided. This is the standard analysis for registry, cohort, and occupational studies comparing an observed event count with population expectation.

Usage

standardizedratio(
  data,
  inputMode = "rate",
  observed,
  personTime = NULL,
  refRate = NULL,
  expected = NULL,
  stratum = NULL,
  ratioType = "sir",
  conf_level = 0.95,
  perStratum = TRUE,
  showPlot = TRUE,
  showSummary = FALSE,
  showExplanation = FALSE
)

Arguments

data: The data as a data frame (one row per stratum).
inputMode: Whether expected events are computed from a reference rate times person-time, or supplied directly as a column of expected counts.
observed: Observed number of events in each stratum.
personTime: Person-time at risk in each stratum (used when expected events are computed from a reference rate).
refRate: Reference-population event rate for each stratum, expressed per person-time unit (used with inputMode = "rate").
expected: Directly supplied expected events per stratum (used with inputMode = "expected").
stratum: Optional stratum label used to report a per-stratum SIR/SMR table.
ratioType: Whether to label results as a standardized incidence or mortality ratio.
conf_level: Confidence level for the exact Poisson interval.
perStratum: Report the SIR/SMR for each stratum in addition to the overall value.
showPlot: Display a forest plot of the per-stratum and overall SIR/SMR.
showSummary: Display a plain-language summary of the result.
showExplanation: Display an explanation of indirect standardization.

Value

A results object containing:

`results$todo`					a html
`results$overallTable`					a table
`results$stratumTable`					a table
`results$plot`					an image
`results$summary`					a html
`results$explanation`					a html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$overallTable$asDF

as.data.frame(results$overallTable)

Examples

# \donttest{
# Long data: one row per stratum with observed events, person-time,
# and a reference rate (events per person-time unit).
standardizedratio(
    data = mydata,
    observed = "obs_events",
    personTime = "person_years",
    refRate = "reference_rate")
#> Error: object 'mydata' not found
# }