meta.cum: Cumulative meta-analysis of binary data

In rmeta: Meta-Analysis

Description

A cumulative meta-analysis plot shows how evidence has accumulated over time. The ith line in the cumulative meta-analysis plot is the summary produced by a meta-analysis of the first i trials.

Usage

cummeta(ntrt, nctrl, ptrt, pctrl, conf.level = 0.95,
   names = NULL, data= NULL, subset = NULL, 
   na.action = na.fail,
    method = c("meta.MH", "meta.DSL"),
   statistic = "OR")
cummeta.summaries(effects,stderrs, conf.level = 0.95,
   names = NULL,weights=NULL, data= NULL,
   subset = NULL, na.action = get(getOption("na.action")),
   method = c("fixed", "random"), logscale=TRUE)
## S3 method for class 'meta.cum'
plot(x, conf.level = NULL,
    colors = meta.colors(), xlab = NULL, 
    summary.line = TRUE, summary.conf = FALSE,
     main="Cumulative meta-analysis", lwd=1, ...)
## S3 method for class 'meta.cum'
summary(object ,conf.level=NULL,...)

Arguments

ntrt	Number of subjects in treated/exposed group
nctrl	Number of subjects in control group
ptrt	Number of events in treated/exposed group
pctrl	Number of events in control group
effects	Difference between control and treatment group
stderrs	Standard errors of effects
weights	Study weights (see meta.summaries)
names	names or labels for studies
data	data frame to interpret variables
subset	subset of studies to include
na.action	How to handle missing values
method	Which meta-analysis method to use
statistic	"OR" for odds ratio or "RR" for relative risk.
logscale	The effects values are the logarithms of actual effects (for plotting)
x, object	a meta.cum object
...	other graphical arguments for metaplot
conf.level	Coverage for confidence intervals
colors	see meta.colors
xlab	X-axis label
summary.line	Plot a vertical line at the final summary value?
summary.conf	Plot vertical lines at the final confidence interval limits?
main,lwd	graphical parameters

Value

Object of class meta.cum.

See Also

meta.MH,meta.DSL

Examples

data(cochrane)
steroid<-cummeta(n.trt,n.ctrl,ev.trt,ev.ctrl,names=name,data=cochrane,
  statistic="RR",method="meta.MH")
plot(steroid)
summary(steroid)
data(catheter)
b <- meta.DSL(n.trt, n.ctrl, col.trt, col.ctrl, data=catheter,
              names=Name, subset=c(13,6,5,3,12,4,11,1,8,10,2))
d <- cummeta.summaries(b$logs, b$selogs, names=b$names,
                    method="random", logscale=TRUE)
plot(d,summary.conf=TRUE)
summary(d)

Example output

Cumulative meta-analysis
Call: cummeta(ntrt = n.trt, nctrl = n.ctrl, ptrt = ev.trt, pctrl = ev.ctrl, 
    names = name, data = cochrane, method = "meta.MH", statistic = "RR")
------------------------------------
               RR (lower  95% upper)
Auckland     0.61    0.41       0.90
Block        0.57    0.39       0.84
Doran        0.53    0.37       0.75
Gamsu        0.57    0.41       0.78
Morrison     0.55    0.41       0.75
Papageorgiou 0.53    0.39       0.71
Tauesch      0.56    0.43       0.75
------------------------------------
Cumulative meta-analysis
Call: cummeta.summaries(effects = b$logs, stderrs = b$selogs, names = b$names, 
    method = "random", logscale = TRUE)
------------------------------------
           Effect (lower  95% upper)
Tennenberg   0.22    0.10       0.49
Maki         0.35    0.16       0.76
vanHeerden   0.35    0.20       0.61
Hannan       0.43    0.24       0.75
Bach(b)      0.36    0.20       0.66
Heard        0.42    0.27       0.67
Collins      0.36    0.22       0.60
Ciresi       0.41    0.26       0.63
Ramsay       0.44    0.31       0.64
Trazzera     0.45    0.33       0.62
George       0.40    0.28       0.57
------------------------------------

rmeta documentation built on May 2, 2019, 1:10 p.m.