computeTraditionalP: Compute the (traditional) p-value

In EmpiricalCalibration: Routines for Performing Empirical Calibration of Observational Study Estimates

Compute the (traditional) p-value

Description

computeTraditionalP computes the traditional two-sided p-value based on the log of the relative risk and the standard error of the log of the relative risk.

Usage

computeTraditionalP(logRr, seLogRr, twoSided = TRUE, upper = TRUE)

Arguments

logRr	A numeric vector of one or more effect estimates on the log scale
seLogRr	The standard error of the log of the effect estimates. Hint: often the standard error = (log(<lower bound 95 percent confidence interval>) - log(<effect estimate>))/qnorm(0.025)
twoSided	Compute two-sided (TRUE) or one-sided (FALSE) p-value?
upper	If one-sided: compute p-value for upper (TRUE) or lower (FALSE) bound?

Value

The (traditional) p-value.

Examples

data(sccs)
positive <- sccs[sccs$groundTruth == 1, ]
computeTraditionalP(positive$logRr, positive$seLogRr)

EmpiricalCalibration documentation built on Sept. 30, 2024, 9:12 a.m.