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Publications - Abstracts: Simplifying the Personal Network Name Generator: Alternatives to Traditional Multiple and Single Name Generators Abstract
Researchers studying personal networks often collect network data using name generators
and name interpreters. We argue that when studying social support, multiple name
generators ensure that researchers sample from a multidimensional definition of support.
However, because administering multiple name generators is time consuming and
strains respondent motivation, researchers often use single name generators. We compared
network measures obtained from single generators to measures obtained from a
six-item multiple-name generator. Although some single generators provided passable
estimates of some measures, no single generator provided reliable estimates across a
broad spectrum of network measures. We then evaluated two alternative methods of
reducing respondent burden: (1) the MMG, a multiple generator using the two most
robust name generators and (2) the MGRI, a six-item name generator with name interpreters
administered for a random subset of alters. Both the MMG and the MGRI were
more reliable than single generators when measuring size, density, and mean measures
of network composition or activity, though some single name generators were more reliable
for measures consisting of sums or counts.
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