R: Effect-size plot

ESplot {gap} | R Documentation

## Effect-size plot

### Description

The function accepts parameter estimates and their standard errors for a range of models.

### Usage

    ESplot(ESdat,SE=TRUE,logscale=TRUE,alpha=0.05,xlim=c(-2,8),v=1,...)

### Arguments

`ESdat` | A data frame consisting of model id, parameter estimates and standard errors or confidence limits
`SE` | If TRUE, the third column of ESdata contains the standard error estimates
`logscale` | If TRUE, indicates log-scale as appropriate for odds ratio
`alpha` | Type-I error rate used to construct 100(1-alpha) confidence interval
`xlim` | Lower and upper limits of the horizontal axis, roughly corresponding to confidence limits
`...` | Other options for `plot`
`v` | Location of the vertical line

### Author(s)

Jing Hua Zhao

### Examples

    ## Not run:
    # 7-4-2008 MRC-Epid JHZ
    options(stringsAsFactors=FALSE)
    testdata <- data.frame(
                  models=c("Basic model","Adjusted","Moderately adjusted","Heavily adjusted","Other"),
                   logOR=log(c(4.5,3.5,2.5,1.5,1)),
                 SElogOR=c(0.2,0.1,0.2,0.3,0.2)
                )
    ESplot(testdata,v=1)
    title("A fictitious plot")
    # Outcomes A2, B2, C2 in three columns
    # par(mfrow=c(1,3))
    # ESplot(snp_effects[c("snpid","A2_b2","A2_se2")], lty=2, xlim=c(0.7,1.4))
    # snp_effects["snpid"] <- ""
    # ESplot(snp_effects[c("snpid","B2_b2","B2_se2")], lty=2, xlim=c(0.7,1.4))
    # ESplot(snp_effects[c("snpid","C2_b2","C2_se2")], lty=2, xlim=c(0.7,1.4))
    #
    # Quantitative trait, as appropriate for linear regression
    # testdata <- data.frame(modelid, beta, se(beta))
    # ESplot(testdata, logscale=FALSE)
    #
    # Other scenarios
    # OR with CI
    # ESplot(testdata,SE=FALSE)

    ## End(Not run)

[Package gap version 1.2.3-1 Index]