Adaptive Web Sampling
Article first published online: 2 JUN 2006
Volume 62, Issue 4, pages 1224–1234, December 2006
How to Cite
Thompson, S. K. (2006), Adaptive Web Sampling. Biometrics, 62: 1224–1234. doi: 10.1111/j.1541-0420.2006.00576.x
- Issue published online: 2 JUN 2006
- Article first published online: 2 JUN 2006
- Received April 2005. Revised January 2006. Accepted January 2006.
- Adaptive sampling;
- Link-tracing designs;
- Markov chain Monte Carlo;
- Network sampling;
- Spatial sampling
Summary A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.