mmstat4 (version 0.2.0)

association: Association measures

Description

Various association coefficients for nominal and ordinal data; the input formats follows stats::chisq.test().

• concordant concordant pairs

• discordant discordant pairs

• ties.row pairs tied on rows

• ties.col pairs tied on columns

• nom.phi Phi Coefficient

• nom.cc Contingency Coefficient (Pearson's C) and Sakoda' s Adjusted Pearson's C

• nom.TT Tshuprow's T (not meaningful for non-square tables)

• nom.CV Cramer's V (for 2 x 2 tables V = Phi)

• nom.lambda Goodman and Kruskal's Lambda with

  • lambda.cr The row variable is used as independent, the column variable as dependent variable.

  • lambda.rc The column variable is used as independent, the row variable as dependent variable.

  • lambda.symmetric Symmetric Lambda (the mean of both above).

• nom.uncertainty Uncertainty Coefficient (Theil's U) with

  • ucc.cr The row variable is used as independent, the column variable as dependent variable.

  • uc.rc The column variable is used as independent, the row variable as dependent variable.

  • uc.symmetric Symmetric uncertainty coefficient.

• ord.gamma Gamma coefficient

• ord.tau a vector with Kendall-Stuart Tau's

  • tau.a Tau-a (for quadratic tables only)

  • tau.b Tau-b

  • tau.c Tau-c

• ord.somers.d Somers' d

• eta Eta coefficient for nominal/interval data

Usage

concordant(x, y = NULL)
discordant(x, y = NULL)
ties.row(x, y = NULL)
ties.col(x, y = NULL)
nom.phi(x, y = NULL)
nom.cc(x, y = NULL)
nom.TT(x, y = NULL)
nom.CV(x, y = NULL)
nom.lambda(x, y = NULL)
nom.uncertainty(x, y = NULL)
ord.gamma(x, y = NULL)
ord.tau(x, y = NULL)
ord.somers.d(x, y = NULL)
eta(x, y, breaks = NULL)

Value

the association coefficient(s)

Arguments

x

a numeric vector, table or matrix. x and y can also both be factors.
For eta the independent nominal variable (factor or numeric).

y

a numeric vector; ignored if x is a table or matrix. If x is a factor, y should be a factor of the same length.
For eta the dependent interval variable (numeric).

breaks

either a numeric vector of two or more unique cut points or a single number (greater than or equal to 2) giving the number of intervals into which x is to be cut (only for eta).

Examples

## Nominal data
# remove gender from the table
hec <- apply(HairEyeColor, 1:2, sum)
nom.phi(hec)
nom.cc(hec)
nom.TT(hec)
nom.CV(hec)
nom.lambda(hec)
nom.uncertainty(hec)
## Ordinal data
# create a fake data set
ordx <- sample(5, size=100, replace=TRUE)
ordy <- sample(5, size=100, replace=TRUE)
concordant(ordx, ordy)
discordant(ordx, ordy)
ties.row(ordx, ordy)
ties.col(ordx, ordy)
ord.gamma(ordx, ordy)
ord.tau(ordx, ordy)
ord.somers.d(ordx, ordy)
## Interval/nominal data
eta(iris$Species, iris$Sepal.Length)