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On the index of dissimilarity for lack of fit in loglinear and log-multiplicative models
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Kuha, Jouni and Firth, David (2011) On the index of dissimilarity for lack of fit in loglinear and log-multiplicative models. Computational Statistics & Data Analysis, Vol.55 (No.1). pp. 375-388. doi:10.1016/j.csda.2010.05.005 ISSN 0167-9473.
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Official URL: http://dx.doi.org/10.1016/j.csda.2010.05.005
Abstract
The index of dissimilarity, often denoted by Delta, is commonly used, especially in social science and with large datasets, to describe the lack of fit of models for categorical data. The definition and sampling properties of the index for general loglinear and log-multiplicative models are investigated. It is argued that in some applications a standardized version of the index is appropriate for interpretation. A simple, approximate variance formula is derived for the index, whether standardized or not. A simple bias reduction formula is also given. The accuracy of these formulae and of confidence intervals based upon them is investigated in a simulation study based on large-scale social mobility data. (C) 2010 Elsevier B.V. All rights reserved.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QA Mathematics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Iterative methods (Mathematics), Mathematical models, Log-linear models, Sampling (Statistics), Probability measures | ||||
Journal or Publication Title: | Computational Statistics & Data Analysis | ||||
Publisher: | Elsevier Science Ltd | ||||
ISSN: | 0167-9473 | ||||
Official Date: | 1 January 2011 | ||||
Dates: |
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Volume: | Vol.55 | ||||
Number: | No.1 | ||||
Number of Pages: | 14 | ||||
Page Range: | pp. 375-388 | ||||
DOI: | 10.1016/j.csda.2010.05.005 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | Economic and Social Research Council (Great Britain) (ESRC) |
Data sourced from Thomson Reuters' Web of Knowledge
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