relevance-package {relevance}R Documentation

Calculate Relevance and Significance Measures

Description

Calculates relevance and significance values for simple models and for many types of regression models. These are introduced in 'Stahel, Werner A.' (2021) "Measuring Significance and Relevance instead of p-values." <https://stat.ethz.ch/~stahel/relevance/stahel-relevance2103.pdf>. These notions are also applied to replication studies, as described in the manuscript 'Stahel, Werner A.' (2022) "'Replicability': Terminology, Measuring Success, and Strategy" available in the documentation.

Details

The DESCRIPTION file:

Package: relevance
Type: Package
Title: Calculate Relevance and Significance Measures
Version: 2.1
Date: 2024-01-24
Author: Werner A. Stahel
Maintainer: Werner A. Stahel <stahel@stat.math.ethz.ch>
Depends: R (>= 3.5.0)
Imports: stats, utils, graphics
Suggests: MASS, survival, knitr
VignetteBuilder: knitr
Description: Calculates relevance and significance values for simple models and for many types of regression models. These are introduced in 'Stahel, Werner A.' (2021) "Measuring Significance and Relevance instead of p-values." <https://stat.ethz.ch/~stahel/relevance/stahel-relevance2103.pdf>. These notions are also applied to replication studies, as described in the manuscript 'Stahel, Werner A.' (2022) "'Replicability': Terminology, Measuring Success, and Strategy" available in the documentation.
License: GPL-2

Index of help topics: 

asinp                   arc sine Transformation
confintF                Confidence Interval for the Non-Central F and
                        Chisquare Distribution
correlation             Correlation with Relevance and Significance
                        Measures
d.blast                 Blasting for a tunnel
d.everest               Data of an 'anchoring' experiment in psychology
d.negposChoice          Data of an 'anchoring' experiment in psychology
d.osc15                 Data from the OSC15 replication study
d.osc15Onesample        Data from the OSC15 replication study, one
                        sample tests
drop1Wald               Drop Single Terms of a Model and Calculate
                        Respective Wald Tests
dropNA                  drop or replace NA values
dropdata                Drop Observations from a Data.frame
formatNA                Print NA values by a Desired Code
getcoeftable            Extract Components of a Fit
inference               Calculate Confidence Intervals and Relevance
                        and Significance Values
last                    Last Elements of a Vector or of a Matrix
logst                   Started Logarithmic Transformation
ovarian                 ovarian
plconfint               Plot Confidence Intervals
plot.inference          Plot Inference Results
print.inference         Print Tables with Inference Measures
relevance-package       Calculate Relevance and Significance Measures
relevance.options       Options for the relevnance Package
replication             Inference for Replication Studies
rlvClass                Relevance Class
rplClass                Reproducibility Class
shortenstring           Shorten Strings
showd                   Show a Part of a Data.frame
sumNA                   Count NAs
termeffects             All Coefficients of a Model Fit
termtable               Statistics for Linear Models, Including
                        Relevance Statistics
twosamples              Relevance and Significance for One or Two
                        Samples

Further information is available in the following vignettes:

relevance-descr 'Calculate Relevance and Significance Measures' (source)

Relevance is a measure that expresses the (scientific) relevance of an effect. The simplest case is a single sample of supposedly normally distributed observations, where interest lies in the expectation, estimated by the mean of the observations. There is a threshold for the expectation, below which an effect is judged too small to be of interest.

The estimated relevance ‘Rle’ is then simply the estimated effect divided by the threshold. If it is larger than 1, the effect is thus judged relevant. The two other values that characterize the relevance are the limits of the confidence interval for the true value of the relevance, called the secured relevance ‘Rls’ and the potential relevance ‘Rlp’.

If Rle > 1, then one might say that the effect is “significantly relevant”.

Another useful measure, meant to replace the p-value, is the “significance” ‘Sg0’. In the simple case, it divides the estimated effect by the critical value of the (t-) test statistic. Thus, the statistical test of the null hypothesis of zero expectation is significant if ‘Sg0’ is larger than one, Sg0 > 1.

These measures are also calculated for the comparison of two groups, for proportions, and most importantly for regression models. For models with linear predictors, relevances are obtained for standardized coefficients as well as for the effect of dropping terms and the effect on prediction.

The most important functions are

twosamples():

calculate the measures for two paired or unpaired sampless or a simple mean. This function calls

inference():

calculates the confidence interval and siginificance based on an estimate and a standard error, and adds relevance for a standardized effect.

termtable():

deals with fits of regression models with a linear predictor. It calculates confidence intervals and significances for the coefficients of terms with a single degree of freedom. It includes the effect of dropping each term (based on the drop1 function) and the respective significance and relevance measures.

termeffects():

calculates the relevances for the coefficients related to each term. These differ from the enties of termtable only for terms with more than one degree of freedom.

Author(s)

Werner A. Stahel

Maintainer: Werner A. Stahel <stahel@stat.math.ethz.ch>

References

Stahel, Werner A. (2021). New relevance and significance measures to replace p-values. To appear in PLoS ONE

See Also

Package regr, avaiable from https://regdevelop.r-forge.r-project.org

Examples

  data(swiss)
  rr <- lm(Fertility ~ . , data = swiss)
  termtable(rr)
[Package relevance version 2.1 Index]