smokingcessation: Stochastic Search Inconsistency Factor Selection of...

In ssifs: Stochastic Search Inconsistency Factor Selection

Stochastic Search Inconsistency Factor Selection of interventions for smoking cessation

Description

Stochastic Search Inconsistency Factor Selection for the evaluation of the consistency assumption for the network meta-analysis model.

These data are used as an example in Dias et al. (2013).

Format

A data frame with the following columns:

event1	number of individuals with successful smoking cessation in arm 1
n1	number of individuals in arm 1
event2	number of individuals with successful smoking cessation in arm 2
n2	number of individuals in arm 2
event3	number of individuals with successful smoking cessation in arm 3
n3	number of individuals in arm 3
treat1	treatment 1
treat2	treatment 2
treat3	treatment 3

Source

Dias S, Welton NJ, Sutton AJ, Caldwell DM, Lu G and Ades AE (2013): Evidence Synthesis for Decision Making 4: Inconsistency in networks of evidence based on randomized controlled trials. Medical Decision Making, 33, 641–56

Examples

data(smokingcessation)

# Transform data from arm-based format to contrast-based format

smokingcessation$id <- 1:dim(smokingcessation)[1]
smoking.pair <- meta::pairwise(
  treat = list(treat1, treat2, treat3),
  event = list(event1, event2, event3),
  n = list(n1, n2, n3),
  studlab = id,
  data = smokingcessation,
  sm = "OR"
)

TE <- smoking.pair$TE
seTE <- smoking.pair$seTE
studlab <- smoking.pair$studlab
treat1 <- smoking.pair$treat1
treat2 <- smoking.pair$treat2

# Stochastic Search Inconsistency Factor Selection using as reference treatment A and the
# design-by-treatment method for the specification of the Z matrix.

m <- ssifs(TE, seTE, treat1, treat2, studlab, ref = "A",
M = 1000, B = 100, M_pilot = 1000, B_pilot = 100)

ssifs documentation built on April 4, 2025, 4:51 a.m.