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Cross-Level Inference
A01=Christopher H. Achen
A01=W. Phillips Shively
Author_Christopher H. Achen
Author_W. Phillips Shively
Category=JHBC
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Product details
- ISBN 9780226002194
- Weight: 510g
- Dimensions: 20 x 25mm
- Publication Date: 01 May 1995
- Publisher: The University of Chicago Press
- Publication City/Country: US
- Product Form: Hardback
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In the last few years, new disputes have erupted over the use of group averages from census areas or voting districts to draw inferences about individual social behaviour. Social scientists, policy analysts and historians often have little choice about using this kind of data, but statistical analysis of them is fraught with pitfalls. The recent debates have led to a new menu of choices for the applied researcher. This volume explains why older methods like ecological regression so often fail, and it examines the promising new techniques for cross-level inference. Experts in statistical analysis of aggregate data, Christopher H. Achen and W. Philips Shively, contend that cross-level inference makes unusually strong demands on substantive knowledge, so that no one method, such as Goodman's ecological regression, will fit all situations. Criticizing Goodman's model and some recent attempts to replace it, the authors argue for a range of alternate techniques, including extensions of cross-tabular, regression analysis and unobservable variable estimators.
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