margMLECI | R Documentation |
Compute the marginal MLE confidence interval of the ratio of two Poisson rates in a two-sample Poisson rate problem with misclassified data given fallible and infallible datasets.
margMLECI(data, N1, N2, N01, N02, conf.level = 0.95, l = 1e-10, u = 1e+10)
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 |
l |
the lower end of the range of possible phi's (for optim) |
u |
the upper end of the range of possible phi's (for optim) |
a named vector containing the lower and upper bounds of the confidence interval
Kahle, D., P. Young, B. Greer, and D. Young (2016). "Confidence Intervals for the Ratio of Two Poisson Rates Under One-Way Differential Misclassification Using Double Sampling." Computational Statistics & Data Analysis, 95:122–132.
# 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)
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