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A dataset of 25 trials investigating 17 treatments for stroke prevention in atrial fibrillation patients. The main outcome is the number of patients with a stroke, and a covariate captures the proportion of patients with a prior stroke.

Data are take from Table 1 of Cooper et al. (2009), with the following corrections applied: SPAF 3 and AFASAK 2 do not have a treatment 13 arm, and SPAF 1 does not contain treatment 5, but treatment 6. Thanks to prof. Cooper for providing the original analysis dataset.

A network meta-regression dataset containing 60 rows of arm-based data (responders and sample size).

Cooper et al. (2009),
*Adressing between-study heterogeneity and inconsistency in mixed treatment comparisons: Application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation*,
Statistics in Medicine 28:1861-1881.
[doi: 10.1002/sim.3594]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
# Build a model similar to Model 4(b) from Cooper et al. (2009):
classes <- list("control"=c("01"),
"anti-coagulant"=c("02","03","04","09"),
"anti-platelet"=c("05","06","07","08","10","11","12","16","17"),
"mixed"=c("13","14","15"))
regressor <- list(coefficient='shared',
variable='stroke',
classes=classes)
model <- mtc.model(atrialFibrillation,
type="regression",
regressor=regressor,
om.scale=10)
## Not run:
result <- mtc.run(model)
## End(Not run)
``` |

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