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Evaluation of Methods for Ecological Inference
Author(s) -
Cleave N.,
Brown P. J.,
Payne C. D.
Publication year - 1995
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.2307/2983403
Subject(s) - inference , ecology , computer science , mathematics , artificial intelligence , biology
SUMMARY In ecological inference one uses data which are aggregated by areal units to investigate the behaviour of the individuals comprising those units. Aggregated data are readily available in many fields and within a wide variety of data structures. In the structures considered, the aggregate data are characterized by the absence of available data in the internal cells of a cross‐classification. The aim of the ecological methods is to estimate the expected frequencies of such internal cells, which may be conditional on chosen covariates. Four methods of ecological inference are reviewed and their properties and appropriateness considered. These methods are then applied to data for which the internal cells are known and their performances compared.