ES: Calculating the efficient score statistic
In nshi-stat/netiim3: Improved Inference Methods for Network Meta-Analysis

Description Usage Arguments Details Value References Examples

Calculating the efficient score statistic

1	ES(y, S, ml0, mu0, maxitr = 200)

`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.

# 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)