computeTimeStability: Compute stability of outcome rate over time

In OHDSI/SelfControlledCaseSeries: Self-Controlled Case Series

Compute stability of outcome rate over time

Description

Compute stability of outcome rate over time

Usage

computeTimeStability(
  studyPopulation,
  sccsModel = NULL,
  maxRatio = 1.25,
  alpha = 0.05
)

Arguments

studyPopulation	An object created using the createStudyPopulation() function.
sccsModel	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.
maxRatio	The maximum global ratio between the observed and expected count.
alpha	The alpha (type 1 error) used to test for stability.

Details

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.

Value

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.

OHDSI/SelfControlledCaseSeries documentation built on Sept. 7, 2024, 8:24 a.m.