Bland Altman Limit of Agreement Calculation with the presence of repeated measurements where the true value vary

Refer to this blog post for the function var.comp.one.way.model

bland.altman.repeated.vary <- function(fmla, dat)
{
    ## Purpose: Calculate LoA (Limit of Agreement) when data has repeated measurements (true value varies)
    ## Arguments:
    ##    fmla: something like "Difference ~ Subject".
    ##    dat: data frame with "Difference" and "Subject".
    ## Return: LoA
    ## Author: Feiming Chen
    ## Reference:
    ##     Bland, J. Martin, and Douglas G. Altman. "Agreement between methods of measurement with multiple observations per
    ##     individual." Journal of biopharmaceutical statistics 17.4 (2007): 571-582.
    ## ________________________________________________

    ans <- var.comp.one.way.model(fmla, dat)
    s <- ans$VCA$SD[3]
    m <- ans$Mean
    cat("\nMean =", m, ", SD =", s, "\n")
    loa <- c(m - 1.96*s, m + 1.96*s) 
    cat("\n95% Limits of Agreement: (", loa[1], ",", loa[2], ")\n")
    invisible(list(m=m, s=s, loa=loa))
}
if (F) {                                # Unit Test
    dat <- data.frame(Subject = factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3, 3)), A = rnorm(10, 10), B = rnorm(10, 10))
    dat$Difference <- dat$A - dat$B
    fmla <- Difference ~ Subject
    bland.altman.repeated.vary(fmla, dat)
    ## Mean = 0.0997215 , SD = 1.851 
    ## 95% Limits of Agreement: ( -3.528239 , 3.727681 )
}