*! version 1.0 18 June 2014
help for npinfoversion 1.0 (18 June 2014)

Title

npinfo -- Merge network-based nodal characteristics

Table of contents

Syntax
Description
Options
Remarks
Example
Author

Syntax

npinfo varlist, options

Obligatory
id(variable) nodes' unique identifier

npcov(varlist) nodal attributes

replace overwrite data in memory

Optional
dyads(varname) generates dyadic dataset (i.e., edgelist)

Description

For outgoing-ties, denoted by varlist, npinfo eases adding the receiving nodes' information or characteristics. npinfo expects network data in wide-format.
An example should make this clearer. Suppose you surveyed classroom-based friendship networks using five nominations. npinfo now provides
a handy way to add friends' characteristics like sex, age, and so on. Additionally, this wide-format information can be turned into an edgelist.

Options

Obligatory

id(variable) indicates the variable uniquely identifying each sending node.

npcov(varlist) provides the list of nodal attributes to be added to each receiving node.
The number of new variables genereated is the number of variables spanning the network times the number of variables describing the nodal attributes.
New variables are named according to the scheme networkvar_npcov.

replace has to be specified as npinfo alters the data in memory.

Optional

dyads(varname) generates a dyadic dataset (i.e., edgelist). The number of new variables equals the number of variables describing the nodal attributes (as specified in npcov(varlist)).
New variables are named according to the scheme varname_npcov.

Remarks

npinfo marks the source of missing information on nodal attributes. In case of item-nonresponse nodal covariates
exhibit a classical missing (i.e., "."). In case of unit-nonresponse nodal covariates exhibit ".a".

Example

Suppose you have a school-based friendship network with five nominations (friend1-friend5) and want to compute the proportion of students' female friends (sex; coded 0 = male and 1 = female).
You could use npinfo to prepare this computation and add friends' sex to each nominated friend. As the network contains five possible nominations, five new variables are generated.
They are named as a combination of the network variables (i.e., friend1, friend2, ...) and the nodal covariates (i.e., sex) resulting in friend1_sex, friend2_sex, ..., friend5_sex.

. npinfo friend1-friend5, id(id_student) npcov(sex)

. egen female_share = rowmean(friend?_sex)

Authors

Sebastian Pink, University of Mannheim, Germany.