| metaplot {rmeta} | R Documentation | 
Meta-analysis plot (forest plot)
Description
Plot confidence intervals with boxes indicating the sample
size/precision and optionally a diamond indicating a summary
confidence interval. This function is usually called by plot
methods for meta-analysis objects.
Usage
metaplot(mn, se, nn=NULL, labels=NULL, conf.level=0.95,
         xlab="Odds ratio", ylab="Study Reference",xlim=NULL,
         summn=NULL, sumse=NULL, sumnn=NULL, summlabel="Summary",
         logeffect=FALSE, lwd=2, boxsize=1,
         zero=as.numeric(logeffect), colors=meta.colors(),
         xaxt="s", logticks=TRUE,  ...)
Arguments
| mn | point estimates from studies | 
| se | standard errors of  | 
| nn | precision: box ares is proportional to this.  | 
| labels | labels for each interval | 
| conf.level | Confidence level for confidence intervals | 
| xlab | label for the point estimate axis | 
| ylab | label for the axis indexing the different studies | 
| xlim | the range for the x axis. | 
| summn | summary estimate | 
| sumse | standard error of summary estimate | 
| sumnn | precision of summary estimate | 
| summlabel | label for summary estimate | 
| logeffect | 
 | 
| lwd | line width | 
| boxsize | Scale factor for box size | 
| zero | "Null" effect value | 
| xaxt | use  | 
| logticks | if  | 
.
| colors | see  | 
| ... | Other graphical parameters | 
Value
This function is used for its side-effect.
See Also
forestplot for more flexible plots
plot.meta.DSL,
plot.meta.MH,
plot.meta.summaries
Examples
data(catheter)
a <- meta.MH(n.trt, n.ctrl, col.trt, col.ctrl, data=catheter,
             names=Name, subset=c(13,6,5,3,7,12,4,11,1,8,10,2))
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
         summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
         logeffect=TRUE)
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
         summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
         logeffect=TRUE,logticks=FALSE)
## angry fruit salad
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
         summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
         logeffect=TRUE, colors=meta.colors(box="magenta",
             lines="blue", zero="red", summary="orange",
             text="forestgreen"))