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
Install the Package From CRAN
Install the Developer Version
Check out the Examples.
Check out the Article on Using Stata for concurve.
"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
- Stark PB, Saltelli A. Cargo-cult statistics and scientific crisis. Significance. 2018;15(4):40-43.
- Poole C. Beyond the confidence interval. Am J Public Health. 1987;77(2):195-199.
- Sullivan KM, Foster DA. Use of the confidence interval function. Epidemiology. 1990;1(1):39-42.
- Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 2012.
- Singh K, Xie M, Strawderman WE. Confidence distribution (CD) – distribution estimator of a parameter. arXiv [mathST]. 2007.
- Schweder T, Hjort NL. Confidence and Likelihood*. Scand J Stat. 2002;29(2):309-332.
- 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
- 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).
- Fraser DAS. The p-value Function and Statistical Inference. Am Stat. 2019
Functions in concurve
|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|
Vignettes of concurve
Last month downloads
|License||GPL-3 | file LICENSE|
|URL||https://data.lesslikely.com/concurve/, https://github.com/Zadchow/concurve, https://lesslikely.com/|
|X-schema.org-keywords||confidence, compatibility, consonance, surprisal, interval, function, curve|
|Packaged||2019-07-10 06:15:29 UTC; Zad|
|Date/Publication||2019-07-10 07:40:03 UTC|
Include our badge in your README