# concurve v2.0

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## Computes and Plots Consonance (Confidence) Intervals, P-Values, and S-Values to Form Consonance and Surprisal Functions

Allows one to compute consonance (confidence) intervals for various statistical tests along with their corresponding P-values and S-values. The intervals can be plotted to create consonance and surprisal functions allowing one to see what effect sizes are compatible with the test model at various consonance levels rather than being limited to one interval estimate such as 95%. These methods are discussed by Poole C. (1987) <doi:10.2105/AJPH.77.2.195>, Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>, Singh K, Xie M, Strawderman WE. (2007) <arXiv:0708.0976>, 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>.

# concurve | Graph Interval Functions

In addition to the overt statistical position, the p-value function also provides easily and accurately many of the familiar types of summary information: a median estimate of the parameter; a one-sided test statistic for a scalar parameter value at any chosen level; the related power function; a lower confidence bound at any level; an upper confidence bound at any level; and confidence intervals with chosen upper and lower confidence limits. The p value reports all the common inference material, but with high accuracy, basic uniqueness, and wide generality.

From a scientific perspective, the likelihood function and p-value function provide the basis for scientific judgments by an investigator, and by other investigators who might have interest. It thus replaces a blunt yes or no decision by an opportunity for appropriate informed judgment.” - D. A. S. Fraser, 2019

# Installation

## For R:

### Install the Package From CRAN

install.packages("concurve")


### Install the Developer Version

library(devtools)


# Dependencies

• ggplot2
• metafor
• parallel
• dplyr
• tibble
• survival
• survminer
• scales

"Statistical software enables and promotes cargo-cult statistics. Marketing and adoption of statistical software are driven by ease of use and the range of statistical routines the software implements. Offering complex and “modern” methods provides a competitive advantage. And some disciplines have in effect standardised on particular statistical software, often proprietary software.

Statistical software does not help you know what to compute, nor how to interpret the result. It does not offer to explain the assumptions behind methods, nor does it flag delicate or dubious assumptions. It does not warn you about multiplicity or p-hacking. It does not check whether you picked the hypothesis or analysis after looking at the data, nor track the number of analyses you tried before arriving at the one you sought to publish – another form of multiplicity. The more “powerful” and “user-friendly” the software is, the more it invites cargo-cult statistics." - Stark & Saltelli, 2018

# References

1. Stark PB, Saltelli A. Cargo-cult statistics and scientific crisis. Significance. 2018;15(4):40-43.
2. Poole C. Beyond the confidence interval. Am J Public Health. 1987;77(2):195-199.
3. Sullivan KM, Foster DA. Use of the confidence interval function. Epidemiology. 1990;1(1):39-42.
4. Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 2012.
5. Singh K, Xie M, Strawderman WE. Confidence distribution (CD) – distribution estimator of a parameter. arXiv [mathST]. 2007.
6. Schweder T, Hjort NL. Confidence and Likelihood*. Scand J Stat. 2002;29(2):309-332.
7. Amrhein V, Trafimow D, Greenland S. Inferential Statistics as Descriptive Statistics: There is No Replication Crisis if We Don’t Expect Replication. Am Stat. 2019
8. Greenland S. Valid P-values Behave Exactly As They Should. Some misleading criticisms of P-values and their resolution with S-values. Am Stat. 2019;18(136).
9. Fraser DAS. The p-value Function and Statistical Inference. Am Stat. 2019

## Functions in concurve

 Name Description curve_corr Computes consonance intervals for correlations plot_concurve Plots the P- (Consonance) and S-Value (Surprisal) Functions using base R graphics. defunct Deprecated functions in concurve. curve_mean Computes consonance intervals for mean differences curve_gen Computes consonance intervals for linear models curve_rev Reverse engineer consonance and surprisal functions from confidence limits and point estimates curve_meta Computes consonance intervals for meta-analysis data curve_surv Produce Consonance Intervals for Survival Data ggconcurve Plots the P-Value (Consonance) and S-value (Surprisal) Function via ggplot2 No Results!

## Vignettes of concurve

 Name figures/function1.png figures/function2.png figures/function3.png figures/function4.png figures/function5.png figures/function6.png figures/graphmenu.png figures/likelihood.png figures/logo.png figures/logo.svg figures/matrix.png figures/statacon.png figures/statacurve.png figures/stataoutput.png figures/statareg.png figures/statascatter.png figures/statasurp.png figures/statasurplog.png examples.Rmd stata.Rmd No Results!