biostudies-literatureDumelle MU.S. Environmental Protection AgencyIntramural EPANational Oceanic and Atmospheric Administration2018-2029https://www.ebi.ac.uk/biostudies/studies/S-EPMC9628259biostudies-literatureUnknown13(9)The design-based and model-based approaches to frequentist statistical inference rest on fundamentally different foundations. In the design-based approach, inference relies on random sampling. In the model-based approach, inference relies on distributional assumptions. We compare the approaches in a finite population spatial context.We provide relevant background for the design-based and model-based approaches and then study their performance using simulated data and real data. The real data is from the United States Environmental Protection Agency's 2012 National Lakes Assessment. A variety of sample sizes, location layouts, dependence structures, and response types are considered. The population mean is the parameter of interest, and performance is measured using statistics like bias, sqMethods in ecology and evolutionA comparison of design-based and model-based approaches for finite population spatial sampling and inference.PMC9628259EPA999999Dumelle MHoef JMVHigham MMadsen LOlsen ARfalseA comparison of design-based and model-based approaches for finite population spatial sampling and inference.The design-based and model-based approaches to frequentist statistical inference rest on fundamentally different foundations. In the design-based approach, inference relies on random sampling. In the model-based approach, inference relies on distributional assumptions. We compare the approaches in a finite population spatial context.We provide relevant background for the design-based and model-based approaches and then study their performance using simulated data and real data. The real data is from the United States Environmental Protection Agency's 2012 National Lakes Assessment. A variety of sample sizes, location layouts, dependence structures, and response types are considered. The population mean is the parameter of interest, and performance is measured using statistics like bias, sq2022-01-01T00:00:00Z2022 Sep2025-04-04T20:04:23.597Z2025-04-04T20:04:23.597ZS-EPMC96282593634086310.1111/2041-210x.1391910.1111/2041-210X.13919