computeMdrr: Compute the minimum detectable relative risk

In OHDSI/SelfControlledCaseSeries: Self-Controlled Case Series

Compute the minimum detectable relative risk

Description

Compute the minimum detectable relative risk

Usage

computeMdrr(
  object,
  exposureCovariateId,
  alpha = 0.05,
  power = 0.8,
  twoSided = TRUE,
  method = "SRL1"
)

Arguments

object	An object either of type SccsIntervalData as created using the createSccsIntervalData function, or an object of type SccsModel as created using the fitSccsModel() function.
exposureCovariateId	Covariate Id for the health exposure of interest.
alpha	Type I error.
power	1 - beta, where beta is the type II error.
twoSided	Consider a two-sided test?
method	The type of sample size formula that will be used. Allowable values are "proportion", "binomial", "SRL1", "SRL2", or "ageEffects". Currently "ageEffects" is not supported.

Details

Compute the minimum detectable relative risk (MDRR) for a given study population, using the observed time at risk and total time in days and number of events. Five sample size formulas are implemented: sampling proportion, binomial proportion, 2 signed root likelihood ratio methods, and likelihood extension for age effects. The expressions by Musonda (2006) are used.

Value

A data frame with the MDRR, number of events, time at risk, and total time.

References

Musonda P, Farrington CP, Whitaker HJ (2006) Samples sizes for self-controlled case series studies, Statistics in Medicine, 15;25(15):2618-31

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