waldCI {poisDoubleSamp} | R Documentation |
Compute the Wald confidence interval
Description
Compute the Wald confidence interval of a two-sample Poisson rate with misclassified data given fallible and infallible datasets.
Usage
waldCI(data, N1, N2, N01, N02, conf.level = 0.95)
Arguments
data |
the vector of counts of the fallible data (z11, z12, z21, z22) followed by the infallible data (m011, m012, m021, m022, y01, y02) |
N1 |
the opportunity size of group 1 for the fallible data |
N2 |
the opportunity size of group 2 for the fallible data |
N01 |
the opportunity size of group 1 for the infallible data |
N02 |
the opportunity size of group 2 for the infallible data |
conf.level |
confidence level of the interval |
Value
a named vector containing the lower and upper bounds of the confidence interval
Examples
# small example
z11 <- 34; z12 <- 35; N1 <- 10;
z21 <- 22; z22 <- 31; N2 <- 10;
m011 <- 9; m012 <- 1; y01 <- 3; N01 <- 3;
m021 <- 8; m022 <- 8; y02 <- 2; N02 <- 3;
data <- c(z11, z12, z21, z22, m011, m012, m021, m022, y01, y02)
waldCI(data, N1, N2, N01, N02)
margMLECI(data, N1, N2, N01, N02)
profMLECI(data, N1, N2, N01, N02)
approxMargMLECI(data, N1, N2, N01, N02)
## Not run:
# big example :
z11 <- 477; z12 <- 1025; N1 <- 16186;
z21 <- 255; z22 <- 1450; N2 <- 18811;
m011 <- 38; m012 <- 90; y01 <- 15; N01 <- 1500;
m021 <- 41; m022 <- 200; y02 <- 9; N02 <- 2500;
data <- c(z11, z12, z21, z22, m011, m012, m021, m022, y01, y02)
waldCI(data, N1, N2, N01, N02)
margMLECI(data, N1, N2, N01, N02)
profMLECI(data, N1, N2, N01, N02)
approxMargMLECI(data, N1, N2, N01, N02)
## End(Not run)
[Package poisDoubleSamp version 1.1.1 Index]