SetMetrics {rankinma}

Setup data of treatment ranking metrics for rankinma

Description

SetMetrics() is a function for checking and preparing data set of metrics for further ploting in rankinma.

Usage

SetMetrics(
  data,
  outcome = NULL,
  tx = NULL,
  metrics = NULL,
  metrics.name = NULL,
  trans = 0.8
)

Arguments

data

DATAFRAME of treatment, metrics, and name of outcomes.

outcome

VARIABLE string data for of outcome(s).

tx

VARIABLE with string data for treatments.

metrics

VARIABLE with numeric data for global metrics, but it should be "NULL" when using "Probabilities" as metrics.

metrics.name

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.

trans

NUMERIC for indicating transparency of colors of treatments.

Value

SetMetrics() returns a confirmed data.frame of treatment, metrics of treatment ranking, and outcome name.

metrics.name

A string shows type of metrics of treatment ranking.

ls.outcome

Strings list outcomes.

ls.tx

Strings list treatments.

n.outcome

An integer shows numbers of outcomes.

n.tx

An integer shows numbers of treatments.

data

A data frame consists of seven columns of core information among all outcomes.

data.sets

A list shows data frame of core information by each outcome.

ptrn.tx

A data frame shows treatments on each outcome.

ptrn.outcome

A data frame shows outcomes by treatments.

color.txs

A data frame shows color of each treatment.

trans

A numeric value shows transparency for colors of each treatment.

See Also

GetMetrics

Examples

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

# Get SUCRA
#nma.1 <- GetMetrics(nma, outcome = "HbA1c.random", prefer = "small", metrics = "SUCRA",
#model = "random", simt = 1000)
#nma.2 <- GetMetrics(nma, outcome = "HbA1c.common", prefer = "small", metrics = "SUCRA",
#model = "common", simt = 1000)

# Combine metrics of multiple outcomes
#dataMetrics <- rbind(nma.1, nma.2)

# Set data for rankinma
#dataRankinma <- SetMetrics(dataMetrics, tx = tx, outcome = outcome,
#metrics = SUCRA, metrics.name = "SUCRA")
## End(Not run)