sgpv

The sgpv package contains functions to calculate second-generation p-values, their associated delta-gaps, and the false discovery risk or false confirmation risk for an alternative or null finding (SGPV = 0 or SGPV = 1) when assumptions are made about the distributions over the null and alternative spaces. It also contains several functions for a variety of plotting types relevant to SGPV usage.

News

Version 1.1.0 updated November 2020, with newly added functions plotman and plotsgpower.

Installation

From CRAN:

install.packages("sgpv")

From GitHub:

# install.packages("devtools")
devtools::install_github("weltybiostat/sgpv")

Example

The sgpvalue() function calculates the second-generation p-value and delta-gap (if applicable) for uncertainty intervals with lower bounds est.lo and upper bounds est.hi and an indifference zone (i.e. interval null hypothesis) of (null.lo, null.hi). Note that this example is in terms of odds ratios, and the second-generation p-value should be calculated on the "symmetric" scale, i.e. log odds ratios in this case.

library(sgpv)
lb = log(c(1.05, 1.3, 0.97))
ub = log(c(1.8, 1.8, 1.02))
sgpvalue(est.lo = lb, est.hi = ub, null.lo = log(1/1.1), null.hi = log(1.1))

# $p.delta
# [1] 0.1220227 0.0000000 1.0000000

# $delta.gap
# [1]       NA 1.752741       NA

References

Introductory paper appearing in the special issue of The American Statisician:

Jeffrey D. Blume, Robert A. Greevy, Valerie F. Welty, Jeffrey R. Smith & William D. Dupont (2019) An Introduction to Second-Generation p-Values, The American Statistician, 73:sup1, 157-167, https://doi.org/10.1080/00031305.2018.1537893

Original proposal appearing in PLoS ONE:

Blume JD, D’Agostino McGowan L, Dupont WD, Greevy RA Jr. (2018). Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses. PLoS ONE 13(3): e0188299. https://doi.org/10.1371/journal.pone.0188299