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- W4294402679 abstract "Estimating proportion of area from a stratified random sample and reference class labels obtained by ground visit or interpretation of satellite imagery is a common strategy in land cover monitoring. Confidence intervals for the proportion of area are typically estimated using the Wald interval, a procedure that is known to yield less than nominal coverage (i.e., undercoverage) when the proportion of area is small (i.e., comprising 10% or less of the region of interest). The practical implication of undercoverage is that confidence intervals will include the true proportion of area for a smaller percent of samples than is implied by the stated confidence level (e.g., 95%). For simple random sampling, alternate confidence interval methods such as Wilson, Agresti-Coull, and Clopper-Pearson have been developed to remedy the undercoverage of the Wald interval, but these methods are not directly applicable to stratified sampling. In this study, we evaluated the Wald interval and two alternative general confidence interval approaches for the case of two strata. One alternative approach, previously proposed in the literature, is based on estimating effective sample size (neff method), whereas the other approach is a new method based on summing stratum-specific confidence bounds (sumstrat method) computed using one of the alternate confidence interval approaches (Wilson, Agresti-Coull, and Clopper-Pearson) for each stratum. The coverage and length of confidence intervals estimated from the different methods were compared using Monte Carlo simulation applied to a set of populations representing diverse conditions of prevalence of the target class and user's and producer's accuracies of the map used to construct the strata. The commonly applied Wald interval achieved coverage well below the nominal 95% confidence for many of the populations evaluated, and the neff method improved upon this undercoverage in only a few populations. The Wilson sumstrat intervals provided the best coverage as this method achieved close to the nominal 95% coverage or greater for most populations. Length of the Wilson sumstrat intervals was comparable to length of other methods. Further study is needed to determine which confidence interval methods are effective when the number of strata exceeds two." @default.
- W4294402679 created "2022-09-03" @default.
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- W4294402679 date "2022-10-01" @default.
- W4294402679 modified "2023-10-11" @default.
- W4294402679 title "Confidence intervals for proportion of area estimated from a stratified random sample" @default.
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- W4294402679 doi "https://doi.org/10.1016/j.rse.2022.113193" @default.
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