Partial and Semi-partial correlation
Calculates a partial or semi-partial correlation with parametric and nonparametric options
partial.cor(
x,
y,
z,
method = c("partial", "semipartial"),
statistic = c("kendall", "pearson", "spearman")
)x |
A vector, data.frame or matrix with 3 columns |
y |
A vector same length as x |
z |
A vector same length as x |
method |
Type of correlation: "partial" or "semipartial" |
statistic |
Correlation statistic, options are: "kendall", "pearson", "spearman" |
Partial and semipartial correlations show the association between two variables when one or more peripheral variables are controlled to hold them constant.
Suppose we have three variables, X, Y, and Z. Partial correlation holds constant one variable when computing the relations two others. Suppose we want to know the correlation between X and Y holding Z constant for both X and Y. That would be the partial correlation between X and Y controlling for Z. Semipartial correlation holds Z constant for either X or Y, but not both, so if we wanted to control X for Z, we could compute the semipartial correlation between X and Y holding Z constant for X.
data.frame containing:
correlation correlation coefficient
p.value p-value of correlation
test.statistic test statistic
n sample size
Method indicating partial or semipartial correlation
Statistic the correlation statistic used
Jeffrey S. Evans <jeffrey_evans@tnc.org>
air.flow = stackloss[,1]
water.temperature = stackloss[,2]
acid = stackloss[,3]
# Partial using Kendall (nonparametric) correlation
partial.cor(air.flow, water.temperature, acid)
scholar <- data.frame(
HSGPA=c(3.0, 3.2, 2.8, 2.5, 3.2, 3.8, 3.9, 3.8, 3.5, 3.1),
FGPA=c(2.8, 3.0, 2.8, 2.2, 3.3, 3.3, 3.5, 3.7, 3.4, 2.9),
SATV =c(500, 550, 450, 400, 600, 650, 700, 550, 650, 550))
# Standard Pearson's correlations between HSGPA and FGPA
cor(scholar[,1], scholar[,2])
# Partial correlation using Pearson (parametric) between HSGPA
# and FGPA, controlling for SATV
partial.cor(scholar, statistic="pearson")
# Semipartial using Pearson (parametric) correlation
partial.cor(x=scholar[,2], y=scholar[,1], z=scholar[,3],
method="semipartial", statistic="pearson")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.