Comparing Measures of Survey Data Quality

描述（由申请人提供）：无回答偏倚的风险是对健康调查有效性的主要威胁。许多专门研究发现，这种偏见可能会影响重要健康措施的结果。不幸的是，关于如何评估无应答偏倚风险的指导很少。许多调查依赖答复率作为关键统计数据。然而，最近的一项荟萃分析表明，应答率是无应答偏倚的不良指标。在所检查的研究中，应答率和无应答偏倚之间几乎没有相关性。缺乏衡量偏见风险的良好指标对健康调查有两方面的危害。第一，高回应率和相对高的无回应偏差的调查可以被接受为有效并发表。第二，低应答率和相对低的无应答偏差的调查可能会受到质疑并被拒绝出版。这两种情况都可能导致关于卫生政策和做法的错误结论。目前的建议试图填补这一空白，通过评估一套指标的风险无反应偏见。每一项衡量标准（包括答复率）都作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点和缺点，以及不正确假设的影响。这些指标进行了比较和对比，通过推导其关键属性。这些属性可以包括如何使用每个度量来对潜在的无响应偏倚设置界限以及这样做所需的假设的描述。此外，还将进行一项模拟研究，以展示每项措施在各种条件下的表现。最后，所有措施都将适用于现有的调查数据收集。拟议项目的目标是帮助制定一套可用于评估无反应偏倚风险的措施的共同理解。这将极大地促进评估与健康有关的调查数据质量的努力。

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.