PSC In The News
Bailey and Dynarski cited in piece on why quality education should be a "civil and moral right"
Kalousova and Burgard find credit card debt increases likelihood of foregoing medical care
Highlights
Arline Geronimus wins Excellence in Research Award from School of Public Health
Yu Xie to give DBASSE's David Lecture April 30, 2013 on "Is American Science in Decline?"
U-M grad programs do well in latest USN&WR "Best" rankings
Sheldon Danziger named president of Russell Sage Foundation
Back in September
Follow us Comparing Measures of Survey Data Quality
a PSC Research Project
Investigators: James Robert Wagner, Michael R. Elliott
The risk of nonresponse bias is a major threat to the validity of health surveys that can impact the results of important health measures. Little guidance is available on 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 nonresponse 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 nonresponse bias may be accepted as valid and published. Second, surveys with low response rates and relatively low nonresponse bias may be questioned and rejected for publication. Both of these situations may lead to incorrect conclusions about health policies and practices.
This project attempts to fill this void by evaluating a set of indicators for the risk of nonresponse 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 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 nonresponse 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 nonresponse bias. This should greatly facilitate efforts to evaluate the quality of health-related survey data.
| Funding: | Eunice Kennedy Shriver National Institute of Child Health and Human Development (1R03HD070012) |
Funding Period: 08/16/2011 to 07/31/2013