getwinloss: Win-loss measures at individual level
In DLEIVA/DyaDA: Dyadic Data Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Function to obtain win and loss measures at individual level from the observed sociomatrix.

1	getwl(X, names=NULL, method=c("Dij","Pij"))

`X`	Empirical sociomatrix containing wins-losses frequencies in dyadic encounters. The matrix must be square and numeric.
`names`	Character vector with the names of individuals. This vector is NULL by default
`method`	A character string indicating which dyadic dominance measure is to be used for the computation of David's scores. One of "Dij" or "Pij", can be abbreviated.

By means of the empirical sociomatrix of wins and losses this function computes several win-loss measures at individual level. Specifically, it computes w, weighted.w, l and weighted.l. w is the sum of individuals' dyadic dominances Dij or the sum of proportions of wins Pij by rows, depending on the specification of the method. weighted.w measures is the sum of individuals' Dij or Pij values weighted by the w values of their interactants. l is the sum of individuals' dyadic dominance indices Dij or the sum of individuals' proportions of wins Pij by columns. And finally, weighted.l is the columns sum of individuals' Dij or Pij values weighted by the l values of their interactants. These measures are used when computing David's scores.

The result is a data frame with the following components:

`w`	Sum of dyadic dominance indices Dij or proportions of wins Pij by rows.
`weighted.w`	Weighted sum of dyadic dominance indices Dij or proportions of wins Pij.
`l`	Sum of dyadic dominance indices Dij or proportions of wins Pij by columns.
`weighted.l`	Weighted sum of dyadic dominance indices Dij or proportions of wins Pij.

David Leiva dleivaur@ub.edu & Han de Vries J.deVries1@uu.nl.

David, H. A. (1988). The Method of Paired Comparisons. London: C. Griffin.

de Vries, H., Stevens, J. M. G., & Vervaecke, H. (2006). Measuring and testing the steepness of dominance hierarchies. Animal Behaviour, 71, 585-592.

getDS.

##############################################################################
###               Example taken from Vervaecke et al. (2007):              ###
##############################################################################

X <- matrix(c(0,58,50,61,32,37,29,39,25,8,0,22,22,9,27,20,10,48,
              3,3,0,19,29,12,13,19,8,5,8,9,0,33,38,35,32,57,
              4,7,9,1,0,28,26,16,23,4,3,0,0,6,0,7,6,12,
              2,0,4,1,4,4,0,5,3,0,2,1,1,5,8,3,0,10,3,1,3,0,0,4,1,2,0),
              nrow=9,byrow=TRUE)

individuals <- c("V","VS","B","FJ","PR","VB","TOR","MU","ZV")

res <- getwinloss(X,names=individuals,method="Dij")

print(res,digits=3)