Errors in reported degrees and respondent driven sampling: implications for bias.
Errors in reported degrees and respondent driven sampling: implications for bias.
复制标题
DOI：
10.1016/j.drugalcdep.2014.06.015
复制
发表时间：
2014-09-01
影响因子：
4.2
通讯作者：
Colijn, Caroline
中科院分区：
文献类型：
--
作者：
Mills, Harriet L.;Johnson, Samuel;Hickman, Matthew;Jones, Nick S.;Colijn, Caroline
受访者驱动抽样（RDS）是一种网络或链式抽样方法，旨在访问难以接触的人群，如注射毒品者（PWID）。RDS调查用于监测一段时间内的行为和感染发生率;这些估计需要调整，以考虑到对有许多接触者的个人的过度采样。调整是根据个人报告的接触总数进行的，假设这些是正确的。在英国布里斯托进行的两次RDS调查中抽样的个人的接触次数（度）数据显示，报告接触次数为5和10的倍数的个人数量大于随机预期。为了模仿这些模式，我们生成了接触网络，并探索了误报程度的不同方法。我们模拟RDS调查，并探讨调整后的估计这些不同的方法的敏感性。我们发现，不准确的报告程度可能会导致大的和可变的偏差估计患病率或发病率。我们的模拟结果表明，配对RDS调查可能高估或低估患病率的任何变化高达25%。这些是特别敏感的不准确的程度估计的个人与谁有低程度。如果没有正确报告度数，则RDS估计值有很大的偏倚风险。这在分析连续RDS样本以评估人口患病率和行为趋势时尤为重要。RDS问卷应进一步完善，以获得高分辨率的信息，特别是从低学位的个人。此外，更大的样本量可以减少估计的不确定性。
Respondent Driven Sampling (RDS) is a network or chain sampling method designed to access individuals from hard-to-reach populations such as people who inject drugs (PWID). RDS surveys are used to monitor behaviour and infection occurence over time; these estimations require adjusting to account for over-sampling of individuals with many contacts. Adjustment is done based on individuals’ reported total number of contacts, assuming these are correct. Data on the number of contacts (degrees) of individuals sampled in two RDS surveys in Bristol, UK, show larger numbers of individuals reporting numbers of contacts in multiples of 5 and 10 than would be expected at random. To mimic these patterns we generate contact networks and explore different methods of mis-reporting degrees. We simulate RDS surveys and explore the sensitivity of adjusted estimates to these different methods. We find that inaccurate reporting of degrees can cause large and variable bias in estimates of prevalence or incidence. Our simulations imply that paired RDS surveys could over- or under-estimate any change in prevalence by as much as 25%. These are particularly sensitive to inaccuracies in the degree estimates of individuals with who have low degree. There is a substantial risk of bias in estimates from RDS if degrees are not correctly reported. This is particularly important when analysing consecutive RDS samples to assess trends in population prevalence and behaviour. RDS questionnaires should be refined to obtain high resolution degree information, particularly from low-degree individuals. Additionally, larger sample sizes can reduce uncertainty in estimates.
登录
查看更多内容
影响因子：
5.4
作者：
Broadhead, RS;Heckathorn, DD;Selwyn, PA
通讯作者：
Selwyn, PA
影响因子：
4.4
作者：
Hope, V. D.;Hickman, M.;Ncube, F.
通讯作者：
Ncube, F.
影响因子：
4.4
作者：
Hickman, Mathew;Hope, Vivian;Annett, Hugh
通讯作者：
Annett, Hugh
DOI：
10.1111/j.1467-9531.2007.00188.x
发表时间：
2007-01-01
期刊：
SOCIOLOGICAL METHODOLOGY 2007, VOL 37
影响因子：
--
作者：
Heckathorn, Douglas D.
通讯作者：
Heckathorn, Douglas D.
影响因子：
3.1
作者：
Lu, Xin
通讯作者：
Lu, Xin