triad.census {sna}R Documentation

Compute the Davis and Leinhardt Triad Census

Description

triad.census returns the Davis and Leinhardt triad census of the elements of dat indicated by g.

Usage

triad.census(dat, g=1:stackcount(dat))

Arguments

dat A graph or graph stack
g The elements of dat to process

Details

The Davis and Leinhardt triad census consists of a classification of all triads into one of 16 different categories; the resulting distribution can be compared against various null models to test for the presence of configural biases (e.g., transitivity bias). triad.census is a front end for the triad.classify routine, performing the classification for all triads within the selected graphs. The results are placed in the order indicated by the column names; this is the same order as presented in the triad.classify documentation, to which the reader is referred for additional details.

Compare triad.census to dyad.census, the dyadic equivalent.

Value

A matrix whose 16 columns contain the counts of triads by class for each graph

Author(s)

Carter T. Butts buttsc@uci.edu

References

Davis, J.A. and Leinhardt, S. (1972). ``The Structure of Positive Interpersonal Relations in Small Groups.'' In J. Berger (Ed.), Sociological Theories in Progress, Volume 2, 218-251. Boston: Houghton Mifflin.

Wasserman, S., and Faust, K. (1994). ``Social Network Analysis: Methods and Applications.'' Cambridge: Cambridge University Press.

See Also

triad.classify, dyad.census, gtrans

Examples

#Generate a triad census of random data with varying densities
triad.census(rgraph(15,5,tprob=c(0.1,0.25,0.5,0.75,0.9)))

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