pma: Pairwise meta-analysis

In audrey-b/BUGSnet: Bayesian network meta-analyses in compliance with best practice and reporting guidelines

Pairwise meta-analysis

Description

implements pairwise meta-analysis via the package meta

Usage

pma(
  data,
  name.trt1,
  name.trt2,
  outcome,
  N,
  sd = NULL,
  time = NULL,
  type.outcome,
  method = "MH",
  method.tau = "DL",
  sm
)

Arguments

data	A BUGSnetData object produced by data.prep()
name.trt1	A string indicating the name of the comparator treatment (often Placebo)
name.trt2	A string indicating the name of the experimental treatment
outcome	A string indicating the name of your outcome variable
N	A string indicating the name of the variable containing the number of participants in each arm
sd	A string (only required when type.outcome="continuous") indicating variable name of the standard deviation of the outcome
time	A string required when type.outcome = "rate". Name of variable indicating person-time followup (e.g person years).
type.outcome	A string. Options are: "binomial", "continuous", "rate" (e.g # of events and # person-years reported)
method	A character string indicating what type of test was used. For more info, see meta's documentation.
method.tau	A character string indicating which method is used to estimate the between study variance. Either "DL", "PM", "REML", "ML", "HS", "SJ", "HE", or "EB", can be abbreviated.
sm	A character string indicating which summary measure ("RR", "OR", "RD", or ASD") is to be used for pooling of studies.

Value

A forest plot as produced by the package meta

raw - dataset containing summary statistics of meta-analysis (effect estimates, confidence bounds, I-squared, Q-statistic)

Note

Depending on the the value of type.outcome, this function will implement the functions metabin (dichotomous outcomes), metacont (continuous outcomes), or metainc (rate outcomes) from the package meta.

See Also

data.prep

Examples

data(diabetes.sim)

diabetes.slr <- data.prep(
  arm.data = diabetes.sim, 
  varname.t = "Treatment", 
  varname.s = "Study"
)

pma(
  data = diabetes.slr,
  type.outcome = "binomial",
  sm = "OR",
  name.trt1 = "Placebo", 
  name.trt2 = "Diuretic", 
  outcome = "diabetes",
  N = "n"
)

audrey-b/BUGSnet documentation built on Feb. 2, 2025, 5:10 p.m.