partialAssociations {CoCoRaw} | R Documentation |
Print on standard output the two dimensional tables with margins, possible for each configuration in the cross classification of other variables, and compute the measures of partial associations on these tables.
partialAssociations(a = "", b = "", c = "", options, data = NULL, object = .object.of.thing(data = data, ...), ...)
a |
A character string with the name of first variable. |
b |
A character string with the name of second variable. |
c |
A character string with the names of variables to condition on. |
options |
A character string with options ,
currently not used. |
data |
See exportCoCo . |
object |
See exportCoCo . |
... |
Additional arguments to generate the CoCo object
from the data argument. See propertyModel . |
TRUE
Jens Henrik Badsberg
Badsberg, J.H.: A guide to CoCo, JSS, 2001 ( http://www.jstatsoft.org/v06/i04/ ) and Badsberg, J.H.: Xlisp+CoCo, Aalborg University, 1996.
library(CoCo); data(HairEyeColor); CoCoObject <- makeCoCo(); enterTable(HairEyeColor, object = CoCoObject); partialAssociations(":Hair:Eye", object = CoCoObject); partialAssociations(":Hair", ":Eye", object = CoCoObject); partialAssociations(":Hair", ":Eye", ":Sex", object = CoCoObject); endCoCo(object = CoCoObject); # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # library(CoCo); data(Reinis); CoCoObject <- makeCoCo(); enterTable(Reinis, object = CoCoObject); partialAssociations("AB", object = CoCoObject); setOrdinal("AB", object = CoCoObject); partialAssociations("AB", object = CoCoObject); # Get Fisher's EXACT test when the total count of the sub table # is less than 1000: partialAssociations("A", "B", "F", object = CoCoObject); endCoCo(object = CoCoObject);