# netsplit

##### Split direct and indirect evidence in network meta-analysis

Split contribution of direct and indirect evidence in network meta-analysis.

##### Usage

`netsplit(x)`# S3 method for netsplit
print(x,
comb.fixed = x$comb.fixed,
comb.random = x$comb.random,
showall = TRUE,
overall = TRUE,
ci = FALSE,
test = TRUE,
digits = gs("digits"),
digits.zval = gs("digits.zval"),
digits.pval = gs("digits.pval"),
text.NA = ".", backtransf = TRUE,
...)

##### Arguments

- x
An object of class

`netmeta`

or`netsplit`

.- comb.fixed
A logical indicating whether results for fixed effect model should be printed.

- comb.random
A logical indicating whether results for random effects model should be printed.

- showall
A logical indicating whether all comparisons (default) or only comparisons contributing both direct and indirect evidence should be printed.

- overall
A logical indicating whether estimates from network meta-analyis should be printed in addition to direct and indirect estimates.

- ci
A logical indicating whether confidence intervals should be printed in addition to treatment estimates.

- test
A logical indicating whether results of a test comparing direct and indirect estimates should be printed.

- digits
Minimal number of significant digits, see

`print.default`

.- digits.zval
Minimal number of significant digits for z-value of test of agreement between direct and indirect evidence, see

`print.default`

.- digits.pval
Minimal number of significant digits for p-value of test of agreement between direct and indirect evidence, see

`print.default`

.- backtransf
A logical indicating whether printed results should be back transformed. For example, if

`backtransf=TRUE`

, results for`sm="OR"`

are printed as odds ratios rather than log odds ratios.- text.NA
A character string specifying text printed for missing values.

- ...
Additional arguments (ignored at the moment)

##### Details

Direct and indirect treatment estimates are calculated in
`netmeta`

. This function combines and prints these
estimates in a user-friendly way.

A comparison of direct and indirect treatment estimates can serve as check for consistency of network meta-analysis (Dias et al., 2010).

##### Value

An object of class `netsplit`

with corresponding
`print`

function. The object is a list containing the following
components:

As defined above.

A vector with treatment comparisons.

A vector with direct evidence proportions (fixed effect / random effects model).

Results of network meta-analysis (fixed effect / random effects model), i.e., list with vectors TE, seTE, lower, upper, z, and p.

Network meta-analysis results based on direct evidence (fixed effect / random effects model), i.e., list with vectors TE, seTE, lower, upper, z, and p.

Network meta-analysis results based on indirect evidence (fixed effect / random effects model), i.e., list with vectors TE, seTE, lower, upper, z, and p.

Comparison of direct and indirect evidence in network meta-analysis (fixed effect / random effects model), i.e., list with vectors TE, seTE, lower, upper, z, and p.

A character string indicating underlying summary measure

The level used to calculate confidence intervals for pooled estimates.

Version of R package netmeta used to create object.

##### References

Dias S, Welton NJ, Caldwell DM, Ades AE (2010).
Checking consistency in mixed treatment comparison meta-analysis.
*Statistics in Medicine*, **29**, 932--44.

Puhan MA, Sch<U+00FC>nemann HJ, Murad MH, et al. (2014).
A GRADE working group approach for rating the quality of treatment
effect estimates from network meta-analysis.
*British Medical Journal*, **349**, g5630

##### See Also

##### Examples

```
# NOT RUN {
data(Woods2010)
#
p1 <- pairwise(treatment, event = r, n = N,
studlab = author, data = Woods2010, sm = "OR")
#
net1 <- netmeta(p1)
#
print(netsplit(net1), digits = 2)
print(netsplit(net1), digits = 2,
backtransf = FALSE, comb.random = TRUE)
data(Senn2013)
#
net2 <- netmeta(TE, seTE, treat1, treat2, studlab, data = Senn2013,
comb.random = TRUE)
#
print(netsplit(net2), digits = 2)
# Layout of Puhan et al. (2014), Table 1
print(netsplit(net2), digits = 2, ci = TRUE, test = FALSE)
# }
```

*Documentation reproduced from package netmeta, version 0.9-5, License: GPL (>= 2)*