dat.yusuf1985 | R Documentation |
Results from studies examining the effectiveness of beta blockers for reducing mortality and reinfarction. \loadmathjax
dat.yusuf1985
The data frame contains the following columns:
table | character | table number |
id | character | trial id number |
trial | character | trial name or first author |
ai | numeric | number of deaths/reinfarctions in treatment group |
n1i | numeric | number of patients in treatment group |
ci | numeric | number of deaths/reinfarctions in control group |
n2i | numeric | number of patients in control group |
The dataset contains table 6 (total mortality from short-term trials of oral beta blockers), 9 (total mortality at one week from trials with an initial IV dose of a beta blocker), 10 (total mortality from long-term trials with treatment starting late and mortality from day 8 onwards in long-term trials that began early and continued after discharge), 11 (nonfatal reinfarction from long-term trials of beta blockers), 12a (sudden death in long-term beta blocker trials), and 12b (nonsudden death in long-term beta blocker trials) from the meta-analysis by Yusuf et al. (1985) on the effectiveness of of beta blockers for reducing mortality and reinfarction.
The article also describes what is sometimes called Peto's one-step method for meta-analyzing \mjeqn2 \times 22x2 table data. This method is implemented in the rma.peto
function.
medicine, cardiology, odds ratios, Peto's method
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Yusuf, S., Peto, R., Lewis, J., Collins, R., & Sleight, P. (1985). Beta blockade during and after myocardial infarction: An overview of the randomized trials. Progress in Cardiovascular Disease, 27(5), 335–371. https://doi.org/10.1016/s0033-0620(85)80003-7
### copy data into 'dat' dat <- dat.yusuf1985 dat[dat$table == 6,] ## Not run: ### load metafor package library(metafor) ### to select a table for the analysis tab <- "6" # either: 6, 9, 10, 11, 12a, 12b ### to double-check total counts as reported in article apply(dat[dat$table==tab,4:7], 2, sum, na.rm=TRUE) ### meta-analysis using Peto's one-step method res <- rma.peto(ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat, subset=(table==tab)) res predict(res, transf=exp, digits=2) ## End(Not run)
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