evalues.RD: Compute E-value for a population-standardized risk difference...

In EValue: Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses

Description

Returns E-values for the point estimate and the lower confidence interval limit for a positive risk difference. If the risk difference is negative, the exposure coding should be first be reversed to yield a positive risk difference.

Usage

evalues.RD(n11, n10, n01, n00, true = 0, alpha = 0.05, grid = 1e-04, ...)

Arguments

n11	Number of exposed, diseased individuals
n10	Number of exposed, non-diseased individuals
n01	Number of unexposed, diseased individuals
n00	Number of unexposed, non-diseased individuals
true	True value of risk difference to which to shift the point estimate. Usually set to 0 to consider the null.
alpha	Alpha level
grid	Spacing for grid search of E-value
...	Arguments passed to other methods.

Examples

## example 1
## Hammond and Holl (1958 JAMA) Data
## Two by Two Table
##          Lung Cancer    No Lung Cancer
##Smoker    397            78557
##Nonsmoker 51             108778

# E-value to shift observed risk difference to 0
evalues.RD(397, 78557, 51, 108778)

# E-values to shift observed risk difference to other null values
evalues.RD(397, 78557, 51, 108778, true = 0.001)

EValue documentation built on Oct. 28, 2021, 9:10 a.m.