Compute stability of outcome rate over time
computeTimeStability(
studyPopulation,
sccsModel = NULL,
maxRatio = 1.25,
alpha = 0.05
)
An object created using the createStudyPopulation()
function.
Optional: A fitted SCCS model as created using fitSccsModel()
. If the
model contains splines for seasonality and or calendar time these will be adjusted
for before computing stability.
The maximum global ratio between the observed and expected count.
The alpha (type 1 error) used to test for stability.
A tibble with one row and three columns: ratio
indicates the estimated mean ratio between observed and expected.
p
is the p-value against the null-hypothesis that the ratio is smaller than maxRatio
, and stable
is TRUE
if p
is greater than alpha
.
Computes for each month the observed and expected count, and computes the (weighted) mean ratio between the two. If
splines are used to adjust for seasonality and/or calendar time, these adjustments are taken into consideration when
considering the expected count. A one-sided p-value is computed against the null hypothesis that the ratio is smaller
than maxRatio
. If this p-value exceeds the specified alpha value, the series is considered stable.