Simplifying the personal network name generator: Alternatives to traditional multiple and single name generators
Simplifying the personal network name generator: Alternatives to traditional multiple and single name generators
复制标题
DOI：
10.1177/1525822x06298588
复制
发表时间：
2007-05-01
期刊：
影响因子：
1.7
通讯作者：
Hampton, Keith N.
中科院分区：
文献类型：
--
作者：
Marin, Alexandra;Hampton, Keith N.
研究个人网络的研究人员经常使用名称生成器和名称翻译器来收集网络数据。我们认为，在研究社会支持时，多个名字生成器确保研究人员从支持的多个维度定义样本。然而，由于管理多个名称生成器非常耗时且抑制了回答动机，研究人员经常使用单一名称生成器。我们比较了从单个生成器获得的网络度量和从六项多名称生成器获得的度量。虽然一些单个生成器对某些度量提供了可接受的估计，但没有单个生成器在广泛的网络度量范围内提供可靠的估计。然后，我们评估了两种减少受访者负担的替代方法：(1)MMG是使用两个最健壮的名称生成器的倍数生成器，以及(2)MGRI，这是一个六项名称生成器，带有针对随机变化子集的名称解释器。在测量网络组成或活动的规模、密度和平均度量时，MMG和MGRI都比单一的生成器更可靠，尽管一些单一名称的生成器对于由总和或计数组成的度量更可靠。
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.