Description Usage Arguments Details Value References Examples
Calculating the efficient score statistic
1 | ES(y, S, ml0, mu0, maxitr = 200)
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y |
N x p matrix of outcome variables. |
S |
Series of within-study covariance matrices of the outcome variables. A matrix or data frame with N rows and p(p+1)/2 columns. |
ml0 |
Initial value of the grand mean vector except for the first component. |
mu0 |
The value of the first component of the grand mean vector. |
maxitr |
The maximum iteration number of the Newton-Raphson algorithm. |
Please see Noma et al. (2017) for details.
The value of the efficient score statistic.
Noma, H., Nagashima, K., Maruo, K., Gosho, M., Furukawa, T. A. (2017). Bartlett-type corrections and bootstrap adjustments of likelihood-based inference methods for network meta-analysis. ISM Research Memorandum 1205.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # dae <- data.aug.edit(smoking)
# y <- dae$y
# S <- dae$S
# beta1e <- 0.80
# ml1 <- ML(y, S)
# a1 <- ml1$Coefficients[, 1]
# a2 <- (ml1$`Between-studies_SD`)^2
# a3 <- a2*(ml1$`Between-studies_COR`)
# a4 <- c(a1, a2, a3)
# beta1 <- log(beta1e)
# ES0 <- ES(y, S, ml0 = a4 , mu0 = beta1)
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