getsignificant: Dyads with significant relationships

In DLEIVA/DyaDA: Dyadic Data Analysis

Description

Function to obtain the number of significant relationships of the observed sociomatrix.

Usage

   getsignificant(X,alpha=0.05,relfreq=TRUE)

Arguments

X	Original sociomatrix.
alpha	Significance level for the binomial test.
relfreq	Logical. If TRUE the function computes percentage of significant relationships.

Details

gettied computes the number of significant dyads in a binomial test at alfa level. The function carries out binomial test for every single cell of the sociomatrix using the frequency in each particular cell as the number of occurrences and the dyadic total of interactions as the total of events.

Value

binom.test.matrix	Matrix with the results of the dyadic binomial tests. Dyadic total number of interactions are shown in the upper triangular part of the matrix, whereas p-values are place in the lower triangular matrix.
tied.dyads	Number of dyads with significant outcomes according to a binomial test.
perc.significant.dyads	Percentage of significant dyads according to a binomial test.

Author(s)

David Leiva <[e-mail]>, Antonio Solanas <[e-mail]>, Han de Vries <[e-mail]>, & David A. Kenny <[e-mail]>.

References

van Hooff, J. A. R. A. M., & Wensing, J. A. B. (1987). Dominance and its behavioral measures in a captive wolf pack. In H. W. Frank (Ed.), Man and wolf (pp. 219-252). Dordrecht: Junk Publishers.

See Also

getonewayrel, gettied, gettwowayrel, getunknown.

Examples

  set.seed(123)
  X <- matrix(floor(runif(20*20,min=0,max=20)),nrow=20,byrow=TRUE)
  diag(X)<-0
  result <- getsignificant(X)
  plot(result)

DLEIVA/DyaDA documentation built on May 6, 2019, 1:17 p.m.