Check if rare outcome assumption is violated
checkRareOutcomeAssumption(
studyPopulation,
firstOutcomeOnly = NULL,
maxPrevalence = 0.1
)A tibble with one row and three columns: outcomeProportion indicates the proportion of people
having the outcome at least once. firstOutcomeOnly indicated whether the analysis was restricted
to the first outcome only. rare is TRUE if the rare outcome assumption is met, or the analysis
was not restricted to the first outcome.
An object created using the createStudyPopulation() function.
Was the analysis restricted to the first outcome only? If left at NULL,
will be determined by whether firstOutcomeOnly was set to TRUE when
calling createStudyPopulation() or whether each person only had one
outcome when pulling the data from the server.
The maximum allowed prevalence (proportion of people with the outcome) allowed when restricting to first outcome only.
Most SCCS analyses restrict to the first outcome occurrence per person to avoid violating the assumption that subsequent occurrences are independent. This is fine, as long as the outcome is rare. According to Farrington et al., the magnitude of the bias from violating this assumption is 0.5p, where p is the prevalence. By default we set the threshold for p at 0.1, corresponding to at most 5 percent bias.
The prevalence was computed in the getDbSccsData() function, within the population defined by
the observation_period table, and restricted to the study period(s) and nesting cohort if
used.
Farrington P, Whitaker H, Ghebremichael-Weldeselassie Y, Self-Controlled Case Series Studies: A Modelling Guide with R, CRC Press, 2018