Mapping raw data can lead to spurious spatial features. For example, regions can appear highly variable because of small sample sizes in spatial sub-units (as in the radon example) or small populations (as in the cancer example), and these apparently variable regions contain a disproportionate number of very high (or low) observed parameter values. Mapping posterior means leads to the reverse problems: areas that appear too uniform because of small sample sizes or populations.
Challenges and Pitfalls in Spatial Data Mapping
| Authors | |
| Year | 1999 |
| Source | All Maps of Parameter Estimates Are Misleading |
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