Description Usage Arguments Author(s) Examples
Confidence intervals for the Potencial Impact Fraction for relative risk inyective functions, the pif is inyective, and intervals can be calculated for log(pif), and then transformed to pif CI.
1 2 3 4 |
X |
Random sample (can be vector or matrix) which includes exposure and covariates. |
thetahat |
Estimative of |
thetavar |
Estimator of variance of thetahat |
rr |
Function for Relative Risk which uses parameter
**Optional** |
cft |
Function |
weights |
Survey |
nsim |
Number of simulations for estimation of variance. |
confidence |
Confidence level % (default 95) |
check_thetas |
Check that theta parameters are correctly inputed |
check_exposure |
Check that exposure |
check_cft |
Check if counterfactual function |
is_paf |
Force evaluation of paf |
Rodrigo Zepeda-Tello rzepeda17@gmail.com
Dalia Camacho-GarcĂa-FormentĂ daliaf172@gmail.com
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | #Example 1: Exponential Relative risk
#--------------------------------------------
set.seed(18427)
X <- rnorm(100,5,1)
thetahat <- 0.4
thetavar <- 0.1
cft <- function(X){sqrt(X)}
pif.confidence.loglinear(X, thetahat, thetavar, rr = function(X, theta){exp(theta*X)}, cft)
#Same example with linear counterfactual
a <- 0.5
cft <- function(X){a*X}
pif.confidence.loglinear(X, thetahat, thetavar, function(X, theta){exp(theta*X)})
#' #Example 2: Multivariate Relative Risk
#--------------------------------------------
set.seed(18427)
X1 <- rnorm(100, 4,0.01)
X2 <- runif(100,0.4,2)
X <- as.matrix(cbind(X1,X2))
thetahat <- c(0.12, 0.03)
thetavar <- matrix(c(0.01, 0, 0, 0.04), byrow = TRUE, nrow = 2)
rr <- function(X, theta){
.X <- as.matrix(X, ncol = 2)
exp(theta[1]*.X[,1] + theta[2]*.X[,2])
}
pif.confidence.loglinear(X, thetahat, thetavar, rr)
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