Summary method for objects of class netcomb.
# S3 method for netcomb
summary(
object,
common = object$common,
random = object$random,
overall.hetstat = object$overall.hetstat,
backtransf = object$backtransf,
nchar.comps = object$nchar.comps,
warn.deprecated = gs("warn.deprecated"),
...
)A list of class "summary.netcomb" is returned with the following elements:
Total number of studies.
Total number of pairwise comparisons.
Total number of treatments.
Total number of designs (corresponding to the unique set of treatments compared within studies).
Total number of components.
Total number of subnetworks (for discomb).
Treatments included in network meta-analysis.
Number of studies evaluating a treatment.
Number of observations receiving a treatment (if available).
Number of events observed for a treatment (if available).
Study labels coerced into a factor with its levels sorted alphabetically.
Number of arms for each study.
Vector with unique designs present in the network. A design corresponds to the set of treatments compared within a study.
Components included in network meta-analysis.
Number of studies evaluating a component.
Number of observations receiving a component (if available).
Number of events observed for a component (if available).
Results for pairwise comparisons (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).
Results for pairwise comparisons based on common effects NMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p, leverage).
Results for pairwise comparisons based on random effects NMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).
Results for pairwise comparisons based on common effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p, leverage).
Results for pairwise comparisons based on random effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).
Results for components based on common effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p, leverage).
Results for components based on random effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).
Results for available combinations based on common effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p, leverage).
Results for available combinations based on random effects CNMA model (data frame with columns studlab, treat1, treat2, TE, seTE, lower, upper, z, p).
Results for common effects model (a list with elements TE, seTE, lower, upper, z, p).
Results for random effects model (a list with elements TE, seTE, lower, upper, z, p).
Prediction intervals (a list with elements seTE, lower, upper).
Overall heterogeneity / inconsistency statistic.
Degrees of freedom for test of heterogeneity / inconsistency.
P-value for test of heterogeneity / inconsistency.
I-squared, lower and upper confidence limits.
Square-root of between-study variance.
Overall heterogeneity / inconsistency statistic (CNMA model).
Degrees of freedom for test of heterogeneity / inconsistency (CNMA model).
P-value for test of heterogeneity / inconsistency (CNMA model).
Overall heterogeneity statistic (NMA model).
Degrees of freedom for test of overall heterogeneity (NMA model).
P-value for test of overall heterogeneity (NMA model).
Q statistic for difference between CNMA and NMA model.
Corresponding degrees of freedom and p-value.
A character string indicating underlying summary measure.
A character string indicating which method is to be used for pooling of studies.
The level used to calculate confidence intervals for individual studies.
The level used to calculate confidence intervals for pooled estimates.
Label for confidence interval.
As defined above.
As defined above.
A character specifying the sequence of treatments.
An optional value for the square-root of the between-study variance \(\tau^2\).
A character used in comparison names as separator between component labels.
A numeric defining the minimum number of characters used to create unique component names.
As defined above.
Title of meta-analysis / systematic review.
netmeta object (if available).
Function call.
Version of R package netmeta used to create object.
An object of class netcomb.
A logical indicating whether results for the common effects model should be printed.
A logical indicating whether results for the random effects model should be printed.
A logical indicating whether to print heterogeneity measures.
A logical indicating whether results should be back transformed in printouts and forest plots.
A numeric defining the minimum number of characters used to create unique component names.
A logical indicating whether warnings should be printed if deprecated arguments are used.
Additional arguments (to catch deprecated arguments).
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
netcomb, discomb