The two main and contradicting criteria guiding sampling design are accuracy of estimators and sampling costs. In stratified random sampling, the sample size must be allocated to strata in order to optimize both objectives. In this note we address, following a biobjective methodology, this allocation problem. A two-phase method is proposed to describe the set of Pareto-optimal solutions of this...

BACKGROUND Typically, a two-phase (double) sampling strategy is employed when classifications are subject to error and there is a gold standard (perfect) classifier available. Two-phase sampling involves classifying the entire sample with an imperfect classifier, and a subset of the sample with the gold-standard. METHODOLOGY/PRINCIPAL FINDINGS In this paper we consider an alternative strategy...

Measurement error can lead to substantial bias in regression problems but can be overcome if replicate measures are available; however replication may be expensive. Although there is a substantial literature on use of 2-phase case control studies to address measurement error problems (eg McNamee 2005), less attention has been paid to 2-phase designs for estimation of β in the Normal regression ...

We present a multi-phase variant of adaptive cluster sampling which allows the sampler to control the number of measurements of the variable of interest. A first-phase sample is selected using an adaptive cluster sampling design based on an inexpensive auxiliary variable associated with the survey variable. Then the network structure of the adaptive cluster sample is used to select an ordinary ...

We investigate the hypothesis that the macroscopic properties of a porous material can be determined from limited morphological information. Specifically, we investigate this hypothesis for the Minkowski functionals of two-phase media in 2-D. We look at two methods for generating samples with desired Minkowski functionals: the Gibbs sampler and the Metropolis-Hastings algorithm. The Metropolis-...