GetMetrics {rankinma}

Get treatment ranking metrics from network meta-analysis output

Description

GetMetrics() is a function for gathering metrics of treatment ranking from netmeta output.

Usage

GetMetrics(
  data,
  outcome = NULL,
  prefer = NULL,
  metrics = NULL,
  model = "random",
  simt = 1000,
  rob = NULL
)

Arguments

data

DATA of netmeta output.

outcome

STRING for name of outcome.

prefer

STRING for indicating which direction is beneficial treatment effect in terms of "small" and "large" values in statistic test.

metrics

STRING for metrics of treatment ranking in terms of "SUCRA", "P-score", and "P-best" for the value of surface under the cumulative ranking curve, P-score, and probability of achieving the best treatment.

model

STRING for analysis model in terms of "random" and "common" for random-effects model and common-effect model.

simt

INTEGER for times of simulations to estimate surface under the cumulative ranking curve (SUCRA).

rob

STRING for column name of risk of bias.

Value

GetMetrics() returns a data.frame with three columns, including treatment, metrics of treatment ranking, and outcome name.

References

Rücker, G., & Schwarzer, G. (2015). Ranking treatments in frequentist network meta-analysis works without resampling methods. BMC medical research methodology, 15(1), 1-9.

Salanti, G., Ades, A. E., & Ioannidis, J. P. (2011). Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. Journal of clinical epidemiology, 64(2), 163-171.

See Also

SetMetrics

Examples

## Not run:
#library(netmeta)
#data(Senn2013)
#nma <- netmeta(TE, seTE, treat1, treat2,
#studlab, data = Senn2013, sm = "SMD")

# Get SUCRA
#dataMetrics <- GetMetrics(nma, outcome = "HbA1c", prefer = "small",
#metrics = "SUCRA", model = "random", simt = 1000)

# Get P-score
#dataMetrics <- GetMetrics(nma, outcome = "HbA1c", prefer = "small",
#metrics = "P-score", model = "random", simt = 1000)
## End(Not run)