Accounting for nonignorable unit nonresponse and attrition in panel studies with refreshment samples

Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the refreshment sample itself. As we illustrate, nonignorable unit nonresponse can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences-corrected for panel attrition-are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses for suspected nonignorable unit nonresponse both in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

Duke Scholars

Author Jerome P. Reiter Statistical Science

Author D. Sunshine Hillygus Political Science