corr.complet: Detailed correlation analysis

In NicolasStefaniak/easieR: easieR: A GUI R metapackage.

Detailed correlation analysis

Description

GUI for detailed correlation analysis. May be used in command line

Usage

corr.complet(X=NULL, Y=NULL, Z=NULL,data=NULL,  group=NULL,
          param=c("param", "non param", "Bayes" "robust"), 
           save=F, outlier=c("complete", "id", "removed"),  
           z=NULL, info=T, n.boot=NULL, rscale=0.353, html=T)

Arguments

X	character or vector. First set of variables. These variables will be on the X axis of the plot
Y	character or vector. Second set of variables. These variables will be on the Y axis of the plot
Z	character or vector. Variables that mut be controlled in the analysis
data	name of dataframe in which to find variables
group	character or vector. Factor variable for which analyses must be done by subgroup.
param	character. One or several among "param", "bayes", "non param", and "robust"
save	logical. Save the results in ms word document
outlier	character. One or several among "complete", "id", or "removed"
z	numeric value. Default for outlier is Grubbs test. If z is not NULL, scaled values are used with z as cutoff
info	Logical. Should information be printed in the console when using dialog boxes?
n.boot	number of bootstrap for bayes and robust analyses. Default is 1000
rscale	rscale for the Bayes analyses. Default = 0.353 see details
html	logical. Do you want easieR to output the results in nice html document ?

Details

corr.complet relies on the packages 'psych', 'BayesFactor' and 'ppcor' for performing parmatric and non parametric analyses, as well as Bayes and robust analyses. rscale is based on Morey's recommendation. The value "medium", "wide" and "ultrawide" are also possible.

Value

Descriptive	Descriptive statistics
normality	Shapiro test, Lilliefors test, graphical distribution of residuals and QQplot
Plot	The ggplot scatter plot
Bravais Pearson correlation	The Bravais-Pearon correlation, if robust has been selected, bootstrapped BCa CI are provided
Spearman rho	Spearman's rho, if robust has been selected, bootstrapped BCa CI are provided
Kendal tau	Kendall's tau
Bayes factor	Bayes factor for the analysis
Grubbs test	Grubbs' test allowing to determine whether there are outlier in the analysis

Author(s)

Nicolas Stefaniak

References

Canty, A, & Ripley, B. (2019). boot: Bootstrap R (S-Plus) Functions. R package version 1.3-23.

Efron, B., & Gong, G. (1983). A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation. *The American Statistician, 371*, 36-48.

Jeffreys, H. (1961). Theory of probability, 3rd edn. Oxford, UK: Oxford University Press.

Richard D. Morey and Jeffrey N. Rouder (2018). BayesFactor: Computation of Bayes Factors for Common Designs. R package version 0.9.12-4.2. https://CRAN.R-project.org/package=BayesFactor

Examples

data(iris)          
corr.complet() # open GUI

corr.complet(X=c('Sepal.Length','Sepal.Width'), Y=c('Petal.Length','Petal.Width'), 
    Z =NULL,data=iris, group=c('Species'), param=c('param','non param','robust','bayes'), 
    save=FALSE,outlier=c('complete','id','removed'),z=NULL, info=T, rscale=0.353553390593274, n.boot=1000, html=TRUE)

NicolasStefaniak/easieR documentation built on Jan. 31, 2025, 2:59 p.m.