Efficient Use of Commercial Lists in U.S. Household Sampling
Richard Valliant1, Frost Hubbard1, Sunghee Lee1
1Institute for Social Research, University of Michigan.
Journal of Survey Statistics and Methodology
|August 8, 2017
Summary
Using incomplete commercial lists for household sampling can improve efficiency in locating specific demographic subgroups. This study explores nonlinear programming for optimal sample allocation under practical constraints.
Area of Science:
- Survey methodology
- Statistical sampling
- Demographic research
Background:
- Commercial lists offer cost-effective household sampling and subgroup identification.
- Demographic data on these lists (e.g., age) is often incomplete and inaccurate.
Purpose of the Study:
- To demonstrate how inexact demographic information from commercial lists can enhance sampling efficiency for specific subgroups.
- To illustrate the application of nonlinear programming for optimizing sample allocations under various constraints.
Main Methods:
- Utilizing commercial address lists combined with data from the National Survey of Family Growth and the Health and Retirement Study.
- Applying nonlinear programming to calculate sample allocations to strata defined by list information.
Main Results:
- Inexact demographic data from commercial lists can improve the efficiency of locating certain demographic subgroups during sampling.
- Nonlinear programming effectively determines sample allocations that meet practical sampling constraints.
Conclusions:
- Commercial lists, despite data inaccuracies, can be valuable tools for targeted demographic sampling.
- Nonlinear programming provides a robust method for optimizing complex sample allocation strategies in surveys.
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