Nothing
#' Meta-analysis of studies of the diagnostic test accuracy of FENO
#' for diagnosis of asthma
#'
#' @description
#' Meta-analysis of studies of the diagnostic test accuracy of
#' fractional exhaled nitric oxide (FENO) for diagnosis of asthma.
#'
#' The data were collected for a systematic review by Karrasch et
#' al. (2017) and are published as a supplement (Appendix 1) to
#' Schneider et al. (2017). They have been preprocessed for use in R
#' package \bold{diagmeta}.
#'
#' @name Schneider2017
#'
#' @docType data
#'
#' @format
#' A data frame with the following columns:
#' \tabular{rl}{
#' \bold{\emph{study_id}}\tab numeric study ID \cr
#' \bold{\emph{author}}\tab first author \cr
#' \bold{\emph{year}}\tab year of publication \cr
#' \bold{\emph{group}}\tab information on subgroup \cr
#' \bold{\emph{cutpoint}}\tab cutpoint (FeNO [ppb]) \cr
#' \bold{\emph{tpos}}\tab number of true positives \cr
#' \bold{\emph{fneg}}\tab number of false negatives \cr
#' \bold{\emph{fpos}}\tab number of false positives \cr
#' \bold{\emph{tneg}}\tab number of true negatives \cr
#' }
#'
#' @source
#' Karrasch S, Linde K, Rücker G, Sommer H, Karsch-Volk M,
#' Kleijnen J, Jörres RA, Schneider A (2017):
#' Accuracy of FENO for diagnosing asthma: a systematic review.
#' \emph{Thorax}, \bold{72}, 109e16
#'
#' Schneider A, Linde K, Reitsma JB, Steinhauser S, Rücker G (2017):
#' A novel statistical model for analyzing data of a systematic review
#' generates optimal cutoff values for fractional exhaled nitric oxide
#' for asthma diagnosis.
#' \emph{Journal of Clinical Epidemiology},
#' \bold{92}, 69--78
#'
#' @keywords datasets
#'
#' @examples
#' # FENO dataset
#' #
#' data(Schneider2017)
#'
#' diag1 <- diagmeta(tpos, fpos, tneg, fneg, cutpoint,
#' studlab = paste(author, year, group),
#' data = Schneider2017,
#' log.cutoff = TRUE)
#'
#' plot(diag1)
NULL
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.