R/testdata.R

In POD: Probability of Detection for Qualitative PCR Methods

#' @title Get Test Data
#'
#' @description Some data to test the functionality of the package
#'
#' @param lab A numeric vector indicating from which laboratory the data should be taken.
#'
#' @return If a lab is not NULL, a data.frame with three columns ('X', 'S', 'N') is returned. If lab is NULL, these three columns are supplemented by a fourth column indicating the laboratory.
#'
#' Data grohmann2015collaborative was generated by Grohmann et al. (2015) and has been used as exemplary data by Uhlig et al. (2015) to assess performance of their statistical approach to validate PCR results. 
#' Data sas.logistic was taken from the part of the SAS manual dealing with logistic regression (\url{https://support.sas.com/documentation/onlinedoc/stat/ex_code/132/logiex14.html}).
#'
#' @references
#' Grohmann et al. Accred Qual Assur (2015) 20: 85. https://doi.org/10.1007/s00769-015-1108-5
#' Uhlig et al. Accred Qual Assur (2015) 20: 75. https://doi.org/10.1007/s00769-015-1112-9
#'
#' @name testdata
#' @aliases grohmann2015collaborative sas.logistic
#'
#' @examples
#' x.all <- grohmann2015collaborative()
#' x.5 <- grohmann2015collaborative(5)
#' sas <- sas.logistic()
NULL

#' @rdname testdata
#' @export
grohmann2015collaborative <- function(lab=NULL){
    N <- 6
    X <- c(0.1, 1, 2, 5, 10, 20)
    LAB <- rbind(
        c(0, 3, 5, 5, 6, 6),
        c(0, 4, 6, 6, 6, 6),
        c(1, 0, 5, 6, 6, 6),
        c(0, 4, 3, 6, 6, 6),
        c(0, 0, 5, 6, 6, 6),
        c(0, 4, 6, 6, 6, 6),
        c(0, 5, 6, 6, 6, 6),
        c(0, 5, 6, 6, 6, 6),
        c(0, 6, 4, 6, 6, 6),
        c(0, 2, 5, 6, 6, 6),
        c(0, 1, 6, 6, 6, 6),
        c(0, 4, 6, 6, 6, 6),
        c(0, 4, 4, 6, 6, 6),
        c(0, 3, 3, 5, 6, 6),
        c(0, 6, 5, 6, 6, 6),
        c(0, 2, 6, 6, 6, 6),
        c(1, 4, 6, 5, 6, 6)
    )
    out <- NULL
    if(is.null(lab) || length(lab)>1){
        RNG <- 1:nrow(LAB)
        if( length(lab)>1 ){ RNG <- intersect(RNG, lab) }
        for(i in RNG){
            out <- rbind(out, cbind( i, X, LAB[i,], N ))
        }
        colnames(out) <- c("lab", "X", "S", "N")
    }else{
        out <- cbind( X, LAB[lab,], N )
        colnames(out) <- c("X", "S", "N")
    }

return(as.data.frame(out))
}

#' @rdname testdata
#' @export
sas.logistic <- function(){
  x <- rbind(
    c(1.5, 123, 8),
    c(4.0, 132, 6),
    c(7.5, 182, 18),
    c(12.5, 140, 14),
    c(17.5, 138, 20),
    c(25.0, 161, 39),
    c(35.0, 133, 19),
    c(47.0, 92,25),
    c(60.0, 74,44)
  )
  colnames(x) <- c("X", "N", "S")

return(as.data.frame(x[, c("X", "S", "N")]))
}