Senn2013: Network meta-analysis in diabetes

In guido-s/netmeta: Network Meta-Analysis using Frequentist Methods

Network meta-analysis in diabetes

Description

Network meta-analysis in diabetes comparing effects of a number of drugs on the HbA1c value.

These data are used as an example in Senn et al. (2013) and have been preprocessed for use in R package netmeta.

Format

A data frame with the following columns:

TE	treatment effect
seTE	standard error of treatment effect
treat1	treatment 1
treat2	treatment 2
treat1.long	treatment 1 (full treatment names)
treat2.long	treatment 2 (full treatment names)
studlab	Study label

Details

Treatment labels provided by columns treat1 and treat2 have been abbreviated:

• acar = Acarbose

• benf = Benfluorex

• metf = Metformin

• migl = Miglitol

• piog = Pioglitazone

• plac = Placebo

• rosi = Rosiglitazone

• sita = Sitagliptin

• sulf = Sulfonylurea

• vild = Vildagliptin

Full treatment names are available in columns treat1.long and treat2.long.

Source

Senn S, Gavini F, Magrez D, Scheen A (2013): Issues in performing a network meta-analysis. Statistical Methods in Medical Research, 22, 169–89

See Also

netmeta

Examples

data(Senn2013)
head(Senn2013)

## Not run: 
# Common effects model
#
net1 <- netmeta(TE, seTE, treat1.long, treat2.long, studlab,
  data = Senn2013, sm = "MD", random = FALSE, nchar.trts = 4)
net1
net1$Q.decomp

# Forest plot
#
forest(net1, ref = "plac")

# Comparison with reference group
#
netmeta(TE, seTE, treat1.long, treat2.long,
  studlab, data = Senn2013, reference = "plac")

# Random effects model
#
net2 <- netmeta(TE, seTE, treat1.long, treat2.long, studlab,
  data = Senn2013, common = FALSE)
net2
forest(net2, ref = "plac")

## End(Not run)

guido-s/netmeta documentation built on April 8, 2024, 5:31 a.m.