Comparing Measures of Survey Data Quality

比较调查数据质量的衡量标准

• 批准号: 8174791
• 负责人: James R Wagner
• 金额: $ 7.78万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-16 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8174791
• 关键词: American Medical Association; Attitude; Comprehension; Data; Data Collection; Data Quality; Decision Making; Derivation procedure; Development; Evaluation; Family; Goals; Growth; Health; Health Policy; Health Surveys; Instruction; Journals; Lead; Measures; Meta-Analysis; Methods; Property; Publications; Publishing; Research; Research Personnel; Risk; Simulate; Surveys; Testing; Weight; Work; base; improved; meetings; response; simulation; statistics; theories

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. PUBLIC HEALTH RELEVANCE: 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 regarding how to evaluate the risk of non response bias. The lack of reasonable, commonly-accepted indicators for the risk of bias is harmful to health research in two ways. First, surveys with high response rates and relatively high non response bias may be accepted as valid and published. In this way, biased results may be propagated. 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 an alternative set of indicators for the risk of non response bias. This evaluation includes theoretical derivation of their properties, a simulation study, and application to existing survey data collections.

描述（由申请人提供）：无反应偏差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健康措施的结果。不幸的是，关于如何评估无反应偏倚风险的指导非常少。许多调查都将回复率作为关键统计数据。然而，最近的一项荟萃​​分析表明，响应率并不是无响应偏差的一个不良指标。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。缺乏衡量偏差风险的良好指标会从两个方面对健康调查造成损害。首先，具有高答复率和相对较高的无答复偏差的调查可以被接受为有效并发布。其次，答复率低且无答复偏差相对较低的调查可能会受到质疑并被拒绝发表。这两种情况都可能导致对卫生政策和实践得出错误的结论。本提案试图通过评估一组无反应偏差风险指标来填补这一空白。这些措施（包括响应率）中的每一项都做出了在大多数实际情况下无法测试的假设。这项研究的目的是了解几种替代措施的优点和缺点以及错误假设的影响。通过推导这些指标的关键属性来对它们进行比较和对比。这些属性可以包括如何使用每个度量来限制潜在的无响应偏差以及这样做所需的假设的描述。此外，还将进行模拟研究，以展示每种措施在不同条件下的表现。最后，所有措施都将应用于现有的调查数据收集。拟议项目的目标是帮助对一组可用于评估无反应偏差风险的措施达成共识。这将极大地促进评估健康相关调查数据质量的努力。 公共卫生相关性：无反应偏差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健康措施的结果。不幸的是，关于如何评估无反应偏倚风险的指导非常少。缺乏合理的、普遍接受的偏倚风险指标在两个方面对健康研究有害。首先，具有高答复率和相对较高的无答复偏差的调查可以被接受为有效并发布。通过这种方式，可能会传播有偏见的结果。其次，答复率低且无答复偏差相对较低的调查可能会受到质疑并被拒绝发表。这两种情况都可能导致对卫生政策和实践得出错误的结论。本提案试图通过评估一组替代指标来衡量无反应偏差的风险，从而填补这一空白。该评估包括其属性的理论推导、模拟研究以及对现有调查数据收集的应用。