Nothing
#-------------------------------------------------------------------------------
# mc4_mthds: List of bmad calculation methods (to be used at level 4)
#-------------------------------------------------------------------------------
#' @name MC4_Methods
#' @title List of level 4 multiple-concentration methods for calculating bmad
#'
#' @description
#' \code{mc4_mthds} returns a list of methods to be used
#' during level 4 multiple-concentration processing for calculating bmad
#'
#' @return A list of functions
#'
#' @seealso \code{\link{mc4}}, \code{\link{Method functions}} to query what
#' methods get applied to each aeid
#'
#' @details
#' The functions contained in the list returned by \code{mc4_mthds} take
#' \code{aeids} (a numeric vector of aeid values) and returns a list of expressions
#' to be executed in the \code{mc4} (not exported) function environment. The
#' functions are described here for reference purposes, The
#' \code{mc4_mthds} function is not exported, nor is it intended for use.
#'
#' All available methods are described in the Available Methods section, listed
#' by the type of function and the function/method name.
#'
#' @section Available Methods:
#'
#'
#' Although it does not say so specifically in each description, all methods
#' are applied by aeid.
#'
#' More information about the level 4 multiple-concentration processing is
#' available in the package vignette, "Data_processing."
#'
#' \describe{
#' \item{bmad.aeid.lowconc.twells}{Calculate the baseline median absolute value (bmad) as the
#' median absolute deviation of normalized response values (rep) for test compound wells
#' (wllt = t) with concentration index (cndx) equal to 1 or 2.}
#' \item{bmad.aeid.lowconc.nwells}{Calculate the baseline median absolute value (bmad) as the
#' median absolute deviation of normalized response values (resp) for neutral control wells
#' (wllt = n).}
#' \item{onesd.aeid.lowconc.twells}{Calculate one standard deviation of the normalized response
#' for test compound wells (wllt = t) with a concentration index (cndx) of 1 or 2;
#' \eqn{onesd=\sqrt{\sum{(resp-mean(resp))^{2}}/(n-1)}}{onesd = sqrt(sum((resp - mean
#' resp)^2)/sample size - 1)}. Used to establish BMR and therefore required for tcplfit2
#' processing.}
#' \item{bidirectional.false}{Limits bidirectional fitting and processes data in positive
#' analysis direction only. Use for gain-of-signal or inverted data.}
#' \item{bmad5.onesd16.static}{Replace baseline median absolute deviation
#' (bmad) with 5 and one standard deviation (osd) of the normalized response
#' for test compound wells (wllt = t) with a concentration index (cndx) of 1
#' or 2 with 16. Typically used for binary data where values would otherwise
#' be 0; non-zero values are required for tcplfit2 processing.}
#' }
#'
#' @note
#' This function is not exported and is not intended to be used by the user.
mc4_mthds <- function() {
list(
bmad.aeid.lowconc.twells = function() {
e1 <- bquote(dat[ , bmad := mad(resp[cndx %in% 1:2 & wllt == "t"], na.rm = TRUE)])
list(e1)
},
bmad.aeid.lowconc.nwells = function() {
e1 <- bquote(dat[ , bmad := mad(resp[wllt == "n"], na.rm = TRUE)])
list(e1)
},
onesd.aeid.lowconc.twells = function() {
e1 <- bquote(dat[ , osd := sd(resp[cndx %in% 1:2 & wllt == "t"], na.rm = TRUE)])
list(e1)
},
bidirectional.false = function() {
e1 <- bquote(dat[ ,bidirectional := FALSE])
list(e1)
},
bmad5.onesd16.static = function() {
e1 <- bquote(dat[ , bmad := 5])
e2 <- bquote(dat[ , osd := 16])
list(e1, e2)
}
)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.