glycobrom: Glycopyrronium Bromide dose-response data

In DoseFinding: Planning and Analyzing Dose Finding Experiments

Glycopyrronium Bromide dose-response data

Description

Data from a clinical study evaluating Efficacy and Safety of Four Doses of Glycopyrronium Bromide in Patients With Stable Chronic Obstructive Pulmonary Disease (COPD). This data set was obtained from clinicaltrials.gov (NCT00501852). The study design was a 4 period incomplete cross-over design. The primary endpoint is the trough forced expiratory volume in 1 second (FEV1) following 7 days of Treatment.

Usage

data(glycobrom)

Format

A data frame with 5 summary estimates (one per dose). Variables: A data frame with 5 summary estimates (one per dose). Variables:

dose

a numeric vector containing the dose values

fev1

a numeric vector containing the least square mean per dose

sdev

a numeric vector containing the standard errors of the least square means per dose

n

Number of participants analyzed per treatment group

Details

The data given here are summary estimates (least-square means) for each dose.

Source

http://clinicaltrials.gov/ct2/show/results/NCT00501852

Examples

 ## simulate a full data set with given means and sdv (here we ignore
  ## the original study was a cross-over design, and simulate a parallel
  ## group design)
  simData <- function(mn, sd, n, doses, fixed = TRUE){
    ## simulate data with means (mns) and standard deviations (sd), for
    ## fixed = TRUE, the data set will have observed means and standard
    ## deviations as given in mns and sd
    resp <- numeric(sum(n))
    uppind <- cumsum(n)
    lowind <- c(0,uppind)+1
    for(i in 1:length(n)){
      rv <- rnorm(n[i])
      if(fixed)
        rv <- scale(rv)
      resp[lowind[i]:uppind[i]] <- mn[i] + sd[i]*rv
    }
    data.frame(doses=rep(doses, n), resp=resp)
  }
  data(glycobrom)
  fullDat <- simData(glycobrom$fev1, glycobrom$sdev, glycobrom$n,
                     glycobrom$dose)

DoseFinding documentation built on Sept. 11, 2024, 9:04 p.m.