pvaluefunctions v1.6.0
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Creates and Plots P-Value Functions, S-Value Functions, Confidence Distributions and Confidence Densities
Contains functions to compute and plot confidence distributions, confidence densities, p-value functions and s-value (surprisal) functions for several commonly used estimates. Instead of just calculating one p-value and one confidence interval, p-value functions display p-values and confidence intervals for many levels thereby allowing to gauge the compatibility of several parameter values with the data. These methods are discussed by Infanger D, Schmidt-Trucks<c3><a4>ss A. (2019) <doi:10.1002/sim.8293>; Poole C. (1987) <doi:10.2105/AJPH.77.2.195>; Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>; Bender R, Berg G, Zeeb H. (2005) <doi:10.1002/bimj.200410104> ; Singh K, Xie M, Strawderman WE. (2007) <doi:10.1214/074921707000000102>; Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052); Amrhein V, Trafimow D, Greenland S. (2019) <doi:10.1080/00031305.2018.1543137>; and Greenland S. (2019) <doi:10.1080/00031305.2018.1529625>.
Readme
pvaluefunctions
P-value functions 
Accompanying paper
We published an accompanying paper to illustrate the use of p-value functions:
Infanger D, Schmidt-Trucksäss A. (2019): P value functions: An underused method to present research results and to promote quantitative reasoning. Statistics in Medicine. 38: 4189-4197. doi: 10.1002/sim.8293.
Recreation of the figures in the paper
The code and instructions to reproduce all graphics in our paper can be found in the following GitHub repository: https://github.com/DInfanger/pvalue_functions
Overview
This is the repository for the R-package
pvaluefunctions.
The package contains R functions to create graphics of p-value
functions, confidence distributions, confidence densities, or the
Surprisal value
(S-value) (Greenland
2019).
Installation
You can install the package directly from CRAN by typing
install.packages("pvaluefunctions"). After installation, load it in R
using library(pvaluefunctions).
Dependencies
The function depends on the following R packages, which need to be installed beforehand:
Use the command install.packages(c("ggplot2", "scales", "zipfR",
"pracma")) in R to install those packages.
Examples
For more examples and code, see the vignette.



References
Bender R, Berg G, Zeeb H. (2005): Tutorial: using confidence curves in medical research. Biom J. 47(2): 237-47.
Berrar D (2017): Confidence Curves: an alternative to null hypothesis significance testing for the comparison of classifiers. Mach Learn 106:911-949.
Fraser D. A. S. (2019): The p-value function and statistical inference. Am Stat, 73:sup1, 135-147.
Greenland S (2019): Valid P-Values Behave Exactly as They Should: Some Misleading Criticisms of P-Values and Their Resolution with S-Values. Am Stat, 73sup1, 106-114.
Infanger D, Schmidt-Trucksäss A. (2019): P value functions: An underused method to present research results and to promote quantitative reasoning. Stat Med, 38, 4189-4197. doi: 10.1002/sim.8293.
Poole C. (1987a): Beyond the confidence interval. Am J Public Health. 77(2): 195-9.
Poole C. (1987b) Confidence intervals exclude nothing. Am J Public Health. 77(4): 492-3.
Rosenthal R, Rubin DB. (1994): The counternull value of an effect size: A new statistic. Psychol Sci. 5(6): 329-34.
Schweder T, Hjort NL. (2016): Confidence, likelihood, probability: statistical inference with confidence distributions. New York, NY: Cambridge University Press.
Xie M, Singh K, Strawderman WE. (2011): Confidence Distributions and a Unifying Framework for Meta-Analysis. J Am Stat Assoc 106(493): 320-33. doi: 10.1198/jasa.2011.tm09803.
Xie Mg, Singh K. (2013): Confidence distribution, the frequentist distribution estimator of a parameter: A review. Internat Statist Rev. 81(1): 3-39.
Contact
Session info
#> R version 4.0.2 (2020-06-22)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 19041)
#>
#> Matrix products: default
#>
#> locale:
#> [1] LC_COLLATE=German_Switzerland.1252 LC_CTYPE=German_Switzerland.1252
#> [3] LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C
#> [5] LC_TIME=German_Switzerland.1252
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] pvaluefunctions_1.6.0
#>
#> loaded via a namespace (and not attached):
#> [1] knitr_1.29 magrittr_1.5 tidyselect_1.1.0 munsell_0.5.0
#> [5] colorspace_1.4-1 R6_2.4.1 rlang_0.4.6 dplyr_1.0.0
#> [9] stringr_1.4.0 tools_4.0.2 grid_4.0.2 gtable_0.3.0
#> [13] xfun_0.15 htmltools_0.5.0 ellipsis_0.3.1 yaml_2.2.1
#> [17] digest_0.6.25 tibble_3.0.1 lifecycle_0.2.0 crayon_1.3.4
#> [21] farver_2.0.3 purrr_0.3.4 ggplot2_3.3.2 vctrs_0.3.1
#> [25] glue_1.4.1 evaluate_0.14 rmarkdown_2.3 pracma_2.2.9
#> [29] stringi_1.4.6 compiler_4.0.2 pillar_1.4.4 generics_0.0.2
#> [33] scales_1.1.1 pkgconfig_2.0.3
License
Functions in pvaluefunctions
| Name | Description | |
| conf_dist | Create and Plot P-Value Functions, S-Value Functions, Confidence Distributions and Confidence Densities | |
| No Results! | ||
Vignettes of pvaluefunctions
| Name | ||
| pvaluefun.Rmd | ||
| No Results! | ||
Last month downloads
Details
| Type | Package |
| License | GPL-3 |
| URL | https://github.com/DInfanger/pvaluefunctions |
| VignetteBuilder | knitr |
| Encoding | UTF-8 |
| LazyData | true |
| RoxygenNote | 7.1.0 |
| NeedsCompilation | no |
| Packaged | 2020-06-24 10:56:55 UTC; denis |
| Repository | CRAN |
| Date/Publication | 2020-06-24 11:20:02 UTC |
| suggests | devtools , knitr , rmarkdown |
| imports | ggplot2 (>= 3.3.0) , pracma (>= 2.2.9) , scales (>= 1.1.0) , stats , zipfR (>= 0.6-66) |
| depends | R (>= 3.5.0) |
| Contributors |
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