BCG: BCG Vaccine Data

In HSAUR3: A Handbook of Statistical Analyses Using R (3rd Edition)

BCG Vaccine Data

Description

A meta-analysis on the efficacy of BCG vaccination against tuberculosis (TB).

Usage

data("BCG")

Format

A data frame with 13 observations on the following 7 variables.

Study

an identifier of the study.

BCGTB

the number of subjects suffering from TB after a BCG vaccination.

BCGVacc

the number of subjects with BCG vaccination.

NoVaccTB

the number of subjects suffering from TB without BCG vaccination.

NoVacc

the total number of subjects without BCG vaccination.

Latitude

geographic position of the place the study was undertaken.

Year

the year the study was undertaken.

Details

Bacille Calmette Guerin (BCG) is the most widely used vaccination in the world. Developed in the 1930s and made of a live, weakened strain of Mycobacterium bovis, the BCG is the only vaccination available against tuberculosis today. Colditz et al. (1994) report data from 13 clinical trials of BCG vaccine each investigating its efficacy in the treatment of tuberculosis. The number of subjects suffering from TB with or without BCG vaccination are given here. In addition, the data contains the values of two other variables for each study, namely, the geographic latitude of the place where the study was undertaken and the year of publication. These two variables will be used to investigate and perhaps explain any heterogeneity among the studies.

Source

G. A. Colditz, T. F. Brewer, C. S. Berkey, M. E. Wilson, E. Burdick, H. V. Fineberg and F. Mosteller (1994), Efficacy of BCG vaccine in the prevention of tuberculosis. Meta-analysis of the published literature. Journal of the American Medical Association, 271(2), 698–702.

Examples

  data("BCG", package = "HSAUR3")

  ### sort studies w.r.t. sample size
  BCG <- BCG[order(rowSums(BCG[,2:5])),]

  ### to long format
  BCGlong <- with(BCG, data.frame(Freq = c(BCGTB, BCGVacc - BCGTB, 
                                           NoVaccTB, NoVacc - NoVaccTB),
                  infected = rep(rep(factor(c("yes", "no")), 
                                 rep(nrow(BCG), 2)), 2),
                  vaccined = rep(factor(c("yes", "no")), 
                                 rep(nrow(BCG) * 2, 2)),
                  study = rep(factor(Study, levels = as.character(Study)), 
                              4)))

  ### doubledecker plot
  library("vcd")
  doubledecker(xtabs(Freq ~ study + vaccined + infected, 
                     data = BCGlong))

HSAUR3 documentation built on Sept. 11, 2024, 8:37 p.m.