While unit or questionnaire nonresponse can seriously degrade the quality of any survey, nonparticipation is particularly threatening to a longitudinal survey like the U.S. Census Bureau's Survey of Income and Program Participation (SIPP). To minimize the potential biasing effects of second and subsequent wave attrition from SIPP panels, staff at the Census Bureau perform weight adjustments. These adjustments are designed to make the self-selected subsample of longitudinal respondents more representative of the initial wave one sample. The Bureau's SIPP weight adjustments take the form of post-stratum or weighting class specific multipliers applied to the wave one base sample weight. The associated weighting classes are defined by collapsing cells in a multi-way cross classification of categorical variables until each resulting cell satisfies two conditions: cells are collapsed until the sample size and the estimated response propensity are greater than predefined thresholds.

The Bureau funded research project reported here (Folsom and Witt, 1994) tests a new nonresponse adjustment methodology recently developed at the Research Triangle Institute (RTI) (Folsom, 191). This new method uses weight adjustment multipliers defined at the person level. These multipliers are created by modeling a sample person's response propensity using constrained forms of either a logistic or exponential model. This nonresponse adjustment methodology was tested on data from the 1987 SIPP panel. The goal of this project was to develop a new SIPP nonresponse adjustment that would reduce the attrition bias in cross sectional and longitudinal estimates derived from the survey.