Check whether two factors are crossed or nested
These functions checks whether two factors are (fully) crossed
or nested, i.e. if each level of one factor occurs in combination with
each level of the other factor (is_crossed()) resp. if each
category of the first factor co-occurs with only one category of the
other (is_nested()). is_cross_classified() checks if one
factor level occurs in some, but not all levels of another factor.
is_crossed(f1, f2) is_nested(f1, f2) is_cross_classified(f1, f2)
Logical. For is_crossed(), TRUE if factors are (fully)
crossed, FALSE otherwise. For is_nested(), TRUE if
factors are nested, FALSE otherwise. For is_cross_classified(),
TRUE, if one factor level occurs in some, but not all levels of
another factor.
If factors are nested, a message is displayed to tell whether f1
is nested within f2 or vice versa.
Grace, K. The Difference Between Crossed and Nested Factors. (web)
# crossed factors, each category of # x appears in each category of y x <- c(1,4,3,2,3,2,1,4) y <- c(1,1,1,2,2,1,2,2) # show distribution table(x, y) # check if crossed is_crossed(x, y) # not crossed factors x <- c(1,4,3,2,3,2,1,4) y <- c(1,1,1,2,1,1,2,2) # show distribution table(x, y) # check if crossed is_crossed(x, y) # nested factors, each category of # x appears in one category of y x <- c(1,2,3,4,5,6,7,8,9) y <- c(1,1,1,2,2,2,3,3,3) # show distribution table(x, y) # check if nested is_nested(x, y) is_nested(y, x) # not nested factors x <- c(1,2,3,4,5,6,7,8,9,1,2) y <- c(1,1,1,2,2,2,3,3,3,2,3) # show distribution table(x, y) # check if nested is_nested(x, y) is_nested(y, x) # also not fully crossed is_crossed(x, y) # but partially crossed is_cross_classified(x, y)
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