Design-consistent model-based variances with systematic sampling: a case study with the Danish national Forest inventory

Abstract

To gauge, whether variances in density estimates computed under an assumption of a simple random sampling (SRS) are inflated – when the actual design ensures a spatial balance, we obtained design-consistent, model-based estimators from simulations with replicate samples and anticipated data. Anticipated data is the sum of model-based predictions and a random residual error. Two designs are employed, they bracket the actual design in terms of plot size and number of replicate samples. Results indicate that SRS estimates of uncertainty in ratios of totals have underestimated precision by 30% whereas precision in model-assisted ratios of totals was underestimated by 14%.