dat.hine1989 | R Documentation |
Results from 6 studies evaluating mortality from prophylactic use of lidocaine in acute myocardial infarction.
dat.hine1989
The data frame contains the following columns:
study | numeric | study number |
source | character | source of data |
n1i | numeric | number of patients in lidocaine group |
n2i | numeric | number of patients in control group |
ai | numeric | number of deaths in lidocaine group |
ci | numeric | number of deaths in control group |
Hine et al. (1989) conducted a meta-analysis of death rates in randomized controlled trials in which prophylactic lidocaine was administered to patients with confirmed or suspected acute myocardial infarction. The dataset describes the mortality at the end of the assigned treatment period for control and intravenous lidocaine treatment groups for six studies. The question of interest is whether there is a detrimental effect of lidocaine. Because the studies were conducted to compare rates of arrhythmias following a heart attack, the studies, taken individually, are too small to detect important differences in mortality rates.
The data in this dataset were obtained from Table I in Normand (1999, p. 322).
medicine, cardiology, risk differences
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Normand, S. T. (1999). Meta-analysis: Formulating, evaluating, combining, and reporting. Statistics in Medicine, 18(3), 321–359. https://doi.org/10.1002/(sici)1097-0258(19990215)18:3<321::aid-sim28>3.0.co;2-p
Hine, L. K., Laird, N., Hewitt, P., & Chalmers, T. C. (1989). Meta-analytic evidence against prophylactic use of lidocaine in acute myocardial infarction. Archives of Internal Medicine, 149(12), 2694–2698. https://doi.org/10.1001/archinte.1989.00390120056011
### copy data into 'dat' and examine data dat <- dat.hine1989 dat ## Not run: ### load metafor package library(metafor) ### calculate risk differences and corresponding sampling variances dat <- escalc(measure="RD", n1i=n1i, n2i=n2i, ai=ai, ci=ci, data=dat) dat ### meta-analysis of risk differences using a random-effects model res <- rma(yi, vi, data=dat) res ## End(Not run)
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