Comparing Measures of Survey Data Quality

描述（由申请人提供）：无反应偏倚的风险是健康调查有效性的主要威胁。许多专门研究发现，这种偏见会影响重要卫生措施的结果。不幸的是，关于如何评估无反应偏倚风险的指导很少。许多调查依赖于回复率作为关键统计数据。然而，最近的荟萃分析表明，反应率是一个很差的指标，无反应偏倚。在被检查的研究中，反应率和非反应偏差之间很少或没有相关性。缺乏一个良好的偏差风险指标在两个方面对健康调查有害。首先，具有高回复率和相对较高的非反应偏差的调查可能被接受为有效并发表。其次，低回复率和相对较低的非反应偏倚的调查可能会被质疑和拒绝发表。这两种情况都可能导致关于卫生政策和做法的不正确结论。本建议试图通过评估一套无反应偏倚风险指标来填补这一空白。这些度量（包括响应率）中的每一个都做出了在大多数实际情况下无法检验的假设。本研究的目的是了解几种替代措施的优缺点，以及错误假设的含义。通过推导这些指标的关键属性，对它们进行比较和对比。这些属性可以包括描述如何使用每个测量来为潜在的非响应偏差设置界限以及这样做所需的假设。此外，还将进行模拟研究，以演示每种措施在不同条件下的执行情况。最后，将所有措施应用于现有的调查数据收集。拟议项目的目标是帮助形成对一套可用于评估无反应偏差风险的措施的共同理解。这将极大地促进评价与健康有关的调查数据质量的工作。

DESCRIPTION (provided by applicant): The risk of non response bias is a major threat to the validity of health surveys. Many special studies have found that this bias can impact the results of important health measures. Unfortunately, there is very little guidance about how to evaluate the risk of nonresponse bias. Many surveys rely on the response rate as a key statistic. However, a recent meta-analysis indicates that the response rate is a poor indicator for non response bias. In the studies examined, there was little or no correlation between the response rate and the non response bias. The lack of a good indicator for the risk of bias is harmful to health surveys in two ways. First, surveys with high response rates and relatively high non response bias may be accepted as valid and published. Second, surveys with low response rates and relatively low non response bias may be questioned and rejected for publication. Both of these situations may lead to incorrect conclusions about health policies and practices. The present proposal attempts to fill this void by evaluating a set of indicators for the risk of non response bias. Each of these measures (including the response rate) makes assumptions that are untestable in most practical situations. The goal of this research is to understand the strengths and weaknesses of each of several alternative measures and the implications of incorrect assumptions. These indicators are compared and contrasted through derivation of their key properties. These properties can include a description of how each measure can be used to place bounds on the potential non response bias and the assumptions required to do so. In addition, a simulation study will be conducted to demonstrate how each measure performs under a varied set of conditions. Finally, all the measures will be applied to existing survey data collections. The goal of the proposed project is to aid in the development of a common understanding of a set of measures that can be used to evaluate the risk of non response bias. This should greatly facilitate efforts to evaluate the quality of health-related survey data.