# pval_plot: Plot one-tailed p-values In PublicationBias: Sensitivity Analysis for Publication Bias in Meta-Analyses

## Description

Plots the one-tailed p-values. The leftmost red line indicates the cutoff for one-tailed p-values less than 0.025 (corresponding to "affirmative" studies; i.e., those with a positive point estimate and a two-tailed p-value less than 0.05). The rightmost red line indicates one-tailed p-values greater than 0.975 (i.e., studies with a negative point estimate and a two-tailed p-value less than 0.05). If there is a substantial point mass of p-values to the right of the rightmost red line, this suggests that selection may be two-tailed rather than one-tailed.

## Usage

 `1` ```pval_plot(yi, vi, alpha.select = 0.05) ```

## Arguments

 `yi` A vector of point estimates to be meta-analyzed. The signs of the estimates should be chosen such that publication bias is assumed to operate in favor of positive estimates. `vi` A vector of estimated variances for the point estimates `alpha.select` Alpha-level at which publication probability is assumed to change

## References

1. Mathur MB & VanderWeele TJ (2020). Sensitivity analysis for publication bias in meta-analyses. Journal of the Royal Statistical Society, Series C. Preprint available at https://osf.io/s9dp6/.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ``` # compute meta-analytic effect sizes require(metafor) dat = metafor::escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg) # flip signs since we think publication bias operates in favor of negative effects dat\$yi = -dat\$yi pval_plot( yi = dat\$yi, vi = dat\$vi ) ```

PublicationBias documentation built on July 23, 2020, 1:07 a.m.