correlation.RdProduces measures of association for all variables in a data frame with confidence intervals when available.
correlation(
data = NULL,
printClasses = FALSE,
progress = TRUE,
methodNum = "pearson",
methodOrd = "kendall",
methodNumOrd = "spearman",
methodNumNom = "eta",
methodNumBin = "pearson",
testChisq = "chisq",
ci = FALSE,
conf = 0.95,
R = 1000,
correct = FALSE,
reportIncomplete = TRUE,
na.action = "na.omit",
digits = 3,
pDigits = 4,
...
)A data frame.
If TRUE, prints a table of classes for
all variables.
If TRUE, prints progress bar when bootstrap
methods are called.
The method for the correlation for two numeric variables.
The default is "pearson". Other options are
"spearman" and "kendall".
The method for the correlation for two ordinal variables.
The default is "kendall", with Kendall's tau-c
used. Other option is "spearman".
The method for the correlation of a numeric and
an ordinal variable.
The default is "pearson". Other options are
"spearman" and "kendall".
The method for the correlation of a numeric and a nominal variable.
The default is "eta", which is the square root
of the r-squared value from anova.
The other option is "epsilon", which is the same,
except with the numeric value rank-transformed.
The method for the correlation of a numeric and
a binary variable.
The default is "pearson".
The other option is "glass", which uses the
Glass rank biserial correlation.
The method for the test of two nominal variables.
The default is "chisq". The other option is
"fisher".
If TRUE, calculates confidence intervals
for methods requiring bootstrap.
If FALSE, will return only those
confidence intervals from methods not
requiring bootstrap.
The confidence level for confidence intervals.
The number of replications to use for bootstrap confidence intervals for applicable methods.
Passed to chisq.test.
If FALSE, NA will be reported in cases
where there are instances of the calculation of the
statistic failing during the bootstrap procedure.
If "na.omit", the function will use only
complete cases, assessed on a bivariate basis.
The other option is "na.pass".
The number of decimal places in the output of most statistics.
The number of decimal places in the output for p-values.
Other arguments.
A data frame of variables, association statistics, p-values, and confidence intervals.
It’s important that variables are assigned the correct class to get an appropriate measure of association. That is, factor variables should be of class "factor", not "character". Ordered factors should be ordered factors (and have their levels in the correct order!).
Date variables are treated as numeric.
The default for measures of association tend to be "parametric" type. That is, e.g. Pearson correlation where appropriate.
Nonparametric measures of association will be reported
with the options
methodNum = "spearman", methodNumNom = "epsilon",
methodNumBin = "glass".
Length = c(0.29, 0.25, NA, 0.40, 0.50, 0.57, 0.62, 0.88, 0.99, 0.90)
Rating = factor(ordered=TRUE, levels=c("Low", "Medium", "High"),
x = rep(c("Low", "Medium", "High"), c(3,3,4)))
Color = factor(rep(c("Red", "Green", "Blue"), c(4,4,2)))
Flag = factor(rep(c(TRUE, FALSE, TRUE), c(5,4,1)))
Answer = factor(rep(c("Yes", "No", "Yes"), c(4,3,3)), levels=c("Yes", "No"))
Location = factor(rep(c("Home", "Away", "Other"), c(2,4,4)))
Distance = factor(ordered=TRUE, levels=c("Low", "Medium", "High"),
x = rep(c("Low", "Medium", "High"), c(5,2,3)))
Start = seq(as.Date("2024-01-01"), by = "month", length.out = 10)
Data = data.frame(Length, Rating, Color, Flag, Answer, Location, Distance, Start)
correlation(Data)
#> Var1 Var2 Type N Measure Statistic
#> 1 Length Rating Numeric x Ordinal 9 Spearman 0.935
#> 2 Length Color Numeric x Nominal 9 Eta 0.913
#> 3 Length Flag Numeric x Binary 9 Pearson -0.576
#> 4 Length Answer Numeric x Binary 9 Pearson -0.101
#> 5 Length Location Numeric x Nominal 9 Eta 0.919
#> 6 Length Distance Numeric x Ordinal 9 Spearman 0.935
#> 7 Length Start Numeric x Numeric 9 Pearson 0.959
#> 8 Rating Color Ordinal x Nominal 10 Freeman 0.812
#> 9 Rating Flag Ordinal x Binary 10 Glass rank biserial -0.333
#> 10 Rating Answer Ordinal x Binary 10 Glass rank biserial 0.667
#> 11 Rating Location Ordinal x Nominal 10 Freeman 0.938
#> 12 Rating Distance Ordinal x Ordinal 10 Kendall 0.780
#> 13 Rating Start Ordinal x Numeric 10 Spearman 0.944
#> 14 Color Flag Nominal x Binary 10 Cramer 0.692
#> 15 Color Answer Nominal x Binary 10 Cramer 0.802
#> 16 Color Location Nominal x Nominal 10 Cramer 0.612
#> 17 Color Distance Nominal x Ordinal 10 Freeman 0.812
#> 18 Color Start Nominal x Numeric 10 Eta 0.935
#> 19 Flag Answer Binary x Binary 10 Phi -0.356
#> 20 Flag Location Binary x Nominal 10 Cramer 0.612
#> 21 Flag Distance Binary x Ordinal 10 Glass rank biserial -0.750
#> 22 Flag Start Binary x Numeric 10 Pearson -0.569
#> 23 Answer Location Binary x Nominal 10 Cramer 0.408
#> 24 Answer Distance Binary x Ordinal 10 Glass rank biserial -0.048
#> 25 Answer Start Binary x Numeric 10 Pearson 0.111
#> 26 Location Distance Nominal x Ordinal 10 Freeman 0.781
#> 27 Location Start Nominal x Numeric 10 Eta 0.933
#> 28 Distance Start Ordinal x Numeric 10 Spearman 0.921
#> Lower.CL Upper.CL Test p.value Signif
#> 1 0.716 0.987 cor.test 0.0002 ***
#> 2 0.812 1.000 Anova 0.0047 **
#> 3 -0.897 0.142 cor.test 0.1044 n.s.
#> 4 -0.717 0.603 cor.test 0.7955 n.s.
#> 5 0.827 1.000 Anova 0.0037 **
#> 6 0.716 0.987 cor.test 0.0002 ***
#> 7 0.812 0.992 cor.test 0.0000 ****
#> 8 NA NA Cochran-Armitage 0.0239 *
#> 9 NA NA wilcox.test 0.0708 n.s.
#> 10 NA NA wilcox.test 0.7172 n.s.
#> 11 NA NA Cochran-Armitage 0.0116 *
#> 12 0.641 0.919 Linear by linear 0.0102 *
#> 13 0.775 0.987 cor.test 0.0000 ****
#> 14 NA NA chisq.test 0.0911 n.s.
#> 15 NA NA chisq.test 0.0402 *
#> 16 NA NA chisq.test 0.1117 n.s.
#> 17 NA NA Cochran-Armitage 0.0251 *
#> 18 0.885 0.982 Anova 0.0007 ***
#> 19 NA NA chisq.test 0.2598 n.s.
#> 20 NA NA chisq.test 0.1534 n.s.
#> 21 NA NA wilcox.test 0.0491 *
#> 22 -0.882 0.095 cor.test 0.0862 n.s.
#> 23 NA NA chisq.test 0.4346 n.s.
#> 24 NA NA wilcox.test 1.0000 n.s.
#> 25 -0.557 0.692 cor.test 0.7597 n.s.
#> 26 NA NA Cochran-Armitage 0.0181 *
#> 27 0.883 0.981 Anova 0.0008 ***
#> 28 0.694 0.982 cor.test 0.0002 ***