`nwcontext`

Create a context variable

Syntax

nwcontext 
[netname]
,
attribute(varname)
[stat(statistic)
mode(context)
generate(newvarname)
mat(string)
noweight
replace]


`attribute(varname)`	Attribute variable
`stat`(statistic)	Statistic that is used to calculate context variable for node i from attributes of network neighbors
`mode`(context)	Define network neighbors of node i as either nodes j who receive ties from i, send ties to j or both
`generate(newvarname)`	Required. Name of the context variable to be generated
`mat(string)`	Store the result in a Mata matrix of this name instead of generating a Stata variable
`noweight`	Ignore valued ties and treats all as binary
`replace`	Replace `generate()`’s target variable if it already exists

Description

nwcontext generates a context variable, which holds information about the attribute values of a node’s network neighbors.

For each node the set of network neighbors is specified in mode(), by default context = outgoing. This means that the new context variable newvarname[i] is calculated based on an all values varname[j], for which there is a tie from node i to node j. A network neighborhood of node i can be either 1) all nodes j to whom i has outgoing ties (default), 2) all nodes j from whom i receives incoming ties, or 3) both. In the case of valued ties varname[j] is weighted accordingly.

After that a statistic defined in stat() is calculated from all weigthed varname[j]. By default, the mean is calculated. More formally:

newvarname[i] = stat(varname[j]), for all j with y_ij > 0

When used with the defaults, the command calculates for each node i the mean score of its network neighbors on varname. Valid statistics are: the** mean, the **max, the min, the sum and the sd of varname.

Sometimes, however, one might want to calculate statistics including the attribute of ego. One can achieve this by using the ego-extended version of each statistic (meanego, maxego, minego, sumego and sdego), which are calculated in this way:

newvarname[i] = stat(varname[j]), for all j with y_ij > 0 or j == i

Remarks

In the case of undirected networks, no * mode* option needs to be specified.

By default, nodes with missing attributes are excluded from the calculation.

Examples

This example loads the Florentine marriage data. The variable wealth indicates how rich each family is. ** nwcontext** generates different variables: w_avg = average wealth of network neighbors, w_min = wealth of poorest network neighbor, w_min = wealth of richest network neighbor, w_sd = standard deviation of wealth over network neighbors.

. nwwebuse florentine
. nwcontext flomarriage, attribute(wealth) generate(w_avg)
. nwcontext flomarriage, attribute(wealth) generate(w_min) stat(min)
. nwcontext flomarriage, attribute(wealth) generate(w_max) stat(max)
. nwcontext flomarriage, attribute(wealth) generate(w_sd) stat(sd)
. list w*
hline 8c -hline 10c -hline 10c -hline 10c -hline 10
c wealth w_avg w_min w_max w_sd c
hline 8c -hline 10c -hline 10c -hline 10c -hline 10
1. c 10 103 103 103 0 c
1. c 36 47.66667 8 103 40.33471 c
1. c 55 61.5 20 103 41.5 c
1. c 44 67.66666 8 146 57.86382 c
1. c 20 83.33334 49 146 44.37968 c
hline 8c -hline 10c -hline 10c -hline 10c -hline 10
1. c 32 36 36 36 0 c
1. c 8 42.5 36 48 4.330127 c
1. c 42 8 8 8 0 c
1. c 103 31 10 55 17.26268 c
1. c 48 10 10 10 0 c
hline 8c -hline 10c -hline 10c -hline 10c -hline 10
1. c 49 70 20 146 54.626 c
1. c 3 . . . . c
1. c 27 99 48 146 40.10819 c
1. c 10 75.5 48 103 27.5 c
1. c 146 35 20 49 11.89538 c
hline 8c -hline 10c -hline 10c -hline 10c -hline 10
1. c 48 46 8 103 41.04469 c
hline 8c -hline 10c -hline 10c -hline 10c -hline 10

You can plot the florentine marriage network with wealth as node label to better understand how these values come about:

. nwplot flomarriage, label(wealth)

Supported network types

Binary: yes. Directed: yes, via mode(outgoing|incoming|both|either). Weighted: yes by default (neighbor attribute values weighted by tie strength); noweight treats all ties as binary. Signed: not checked. Two-mode: not checked.

nwcontext