CExch Compares Skvoretz and Agneessens epsilon exchange index scores for two types of ties in two networks conditional on their outdegree distributions and performs a test for difference in those scores using a Monte-Carlo method as described in Agneessens and
Skvoretz (2011)
Usage
CExch(dat1A, dat1B, dat2A, dat2B, nr1000=1000)
Arguments dat1A,dat1B dat2A,dat2B names of files containing network 1 data on ties A and B and network 2 data on ties A and B. Note network and 2 may come from the same group and the ties
A and B in network 1 do not need to be the same as A and B in network 2 nr1000 number of draws in Monte-Carlo simulation, defaulting to 1000
Output
The Skvoretz and Agneessens exchange index values conditional on outdegree and a z-score value for test that the difference between the two values is zero
Examples
#compare the exchange score for advice and friendship to the
#exchange score for friendship and worked with among Lazega's
#lawyers
CExch("c:\\advilaz.txt","c:\\frilaz.txt","c:\\advilaz.txt",
"c:\\cowlaz.txt")

CMult Compares Skvoretz and Agneessens upsilon multiplexity index scores for two types of ties in two networks conditional on their outdegree distributions and performs a test for difference in those scores using a Monte-Carlo method as described in Agneessens and
Skvoretz (2011)
Usage
CMult(dat1A, dat1B, dat2A, dat2B, nr1000=1000)
Arguments dat1A,dat1B dat2A,dat2B names of files containing network 1 data on ties A and B and network 2 data on ties A and B. Note network 1 and 2 may come from the same group and the ties
A and B in network 1 do not need to be the same as A and B in network 2 nr1000 number of draws in Monte-Carlo simulation, defaulting to 1000
Output
The Skvoretz and Agneessens multiplexity index values conditional on outdegree and a z-score value for test that the difference between the two values is zero
Examples
#compare the multiplexity score for advice and friendship to the
#multiplexity score for friendship and worked with among Lazega's
#lawyers
CMult("c:\\advilaz.txt","c:\\frilaz.txt","c:\\advilaz.txt",
"c:\\cowlaz.txt")

CRecip Compares Katz and Powell tau reciprocity index scores in two networks conditional on their outdegree distributions and performs a test for difference in those scores using a
Monte-Carlo method as described in Agneessens and Skvoretz (2011)
Usage
CRecip(dat1, dat2, nr1000=1000)
Arguments dat1,dat2 nr1000 names of files containing network 1 and network 2 data number of draws in Monte-Carlo simulation, defaulting to 1000
Output
The Katz and Powell reciprocity index values conditional on outdegree and a z-score value for test that the difference between the two values is zero
Examples
#compare the reciprocity score for advice to the reciprocity
#score for friendship among Lazega's lawyers
CRecip("c:\\advilaz.txt","c:\\frilaz.txt")

Exch Calculate Skvoretz and Agneessens epsilon exchange index and perform z-score test that observed number of exchanging pairs equals number expected by chance
Usage
Exch(datA, datB, condition=2)
Arguments datA,datB names of files containing data on tie A and data on tie B condition Integer either 1 or 2, with 2 the default selecting the chance distribution for the null hypothesis: 1 = expected number of exchanging pairs calculated conditional only on total numbers of ties, 2 = expected number of exchanging pairs calculated conditional on outdegree distributions
Output
The Skvoretz and Agneessens index value, observed count of exchanging pairs, z-score value for test that observed count does not differ from expected count under null hypothesis
Examples
#calculate exchange score for advice and friendship among
#Lazega's lawyers conditional on total number of advice ties and
#the total number of friendship ties
Exch("c:\\advilaz.txt", "c:\\frilaz.txt", condition=1)

ExchA Calculate Skvoretz and Agneessens epsilon exchange index scores for subgroups defined by a 0/1 dichotomous attribute conditional on outdegree and perform tests for difference in those scores using a Monte-Carlo method as described in Agneessens and
Skvoretz (2011)
Usage
ExchA(datA,datB,adat,nr1000=1000)
Arguments datA,datB names of files containing network data on tie A and network data on tie B adat nr1000 name of file containing attribute data number of draws in Monte-Carlo simulation, defaulting to 1000
Output
Skvoretz and Agneessens exchange index scores conditional on outdegree for within subgroups and between subgroups and the value of statistical tests for null hypothesis of no difference in exchange scores for pairs of values using a Monte-Carlo method
Examples
#calculate exchange scores for advice and friendship among
#Lazega's lawyers by gender
ExchA("c:\\advilaz.txt","c:\\frilaz.txt","c:\\lazgender.txt")

Mult Calculate Skvoretz and Agneessens upsilon multiplexity index and perform z-score test that observed number of multiplex pairs equals number expected by chance
Usage
Mult(datA, datB, condition=2)
Arguments datA,datB names of files containing data on tie A and data on tie B condition Integer either 1 or 2, with 2 the default selecting the chance distribution for the null hypothesis: 1 = expected number of multiplex pairs calculated conditional only on total numbers of ties, 2 = expected number of multiplex pairs calculated conditional on out degree distributions
Output
The Skvoretz and Agneessens index value, observed count of multiplex pairs, z-score value for test that observed count does not differ from expected count under null hypothesis
Examples
#calculate multiplexity score for advice and friendship among
#Lazega's lawyers conditional on total number of advice ties and
#the total number of friendship ties
Mult("c:\\advilaz.txt", "c:\\frilaz.txt", condition=1)

MultA Calculate Skvoretz and Agneessens upsilon multiplexity index scores for subgroups defined by a 0/1 dichotomous attribute conditional on outdegree and perform tests for difference in those scores using a Monte-Carlo method as described in Agneessens and
Skvoretz (2011)
Usage
MultA(datA,datB,adat,nr1000=1000)
Arguments datA,datB names of files containing network data on tie A and network data on tie B adat nr1000 name of file containing attribute data number of draws in Monte-Carlo simulation, defaulting to 1000
Output
Skvoretz and Agneessens multiplexity index scores conditional on outdegree for within subgroups and between subgroups and the value of statistical tests for null hypothesis of no difference in multiplexity scores for pairs of values using a Monte-Carlo method
Examples
#calculate multiplexity scores for advice and friendship among
#Lazega's lawyers by gender
MultA("c:\\advilaz.txt","c:\\frilaz.txt","c:\\lazgender.txt")

Recip Calculate Katz and Powell tau reciprocity index and perform z-score test that observed number of mutual dyads equal number expected by chance
Usage
Recip(dat, condition=2)
Arguments dat name of file containing network data condition Integer either 1 or 2, with 2 the default selecting the chance distribution for the null hypothesis: 1 = expected number of mutual dyads calculated conditional only on total number of ties, 2 = expected number of mutual dyads calculated conditional on out degree distribution
Output
The Katz and Powell index value, observed count of mutual dyads, z-score value for test that observed count does not differ from expected count under null hypothesis
Examples
#calculate reciprocity score for advice among Lazega's lawyers
#conditional on total number of advice ties
Recip("c:\\advilaz.txt", condition=1)

RecipA Calculate Katz and Powell tau reciprocity scores for subgroups defined by a 0/1 dichotomous attribute conditional on outdegree and perform tests for difference in reciprocity scores using a Monte-Carlo method as described in Agneessens and Skvoretz
(2011)
Usage
RecipA(dat,adat,nr1000=1000)
Arguments dat adat nr1000
Output name of file containing network data name of file containing attribute data number of draws in Monte-Carlo simulation, defaulting to 1000
Katz and Powell index scores conditional on outdegree for within subgroups and between subgroups and the value of statistical tests for null hypothesis of no difference in reciprocity scores for pairs of values using a Monte-Carlo method
Examples
#calculate reciprocity scores for advice among Lazega's lawyers
#by gender
RecipA("c:\\advilaz.txt", "c:\\lazgender.txt")