Modeling patterns in count data using loglinear and related models

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Description

This report explains the use of loglinear and logit models, for analyzing Poisson and binomial counts in the presence of explanatory variables. The explanatory variables may be unordered categorical variables or numerical variables, or both. The report shows how to construct models to fit data, and how to test whether a model is too simple or too complex. The appropriateness of the methods with small data sets is discussed. Several example analyses, using the SAS computer package, illustrate the methods.

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100 p.

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Atwood, C.L. December 1, 1995.

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Description

This report explains the use of loglinear and logit models, for analyzing Poisson and binomial counts in the presence of explanatory variables. The explanatory variables may be unordered categorical variables or numerical variables, or both. The report shows how to construct models to fit data, and how to test whether a model is too simple or too complex. The appropriateness of the methods with small data sets is discussed. Several example analyses, using the SAS computer package, illustrate the methods.

Physical Description

100 p.

Notes

INIS; OSTI as DE96004131

Source

  • Other Information: PBD: Dec 1995

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  • Other: DE96004131
  • Report No.: INEL--95/0121
  • Grant Number: AC07-94ID13223
  • DOI: 10.2172/172140 | External Link
  • Office of Scientific & Technical Information Report Number: 172140
  • Archival Resource Key: ark:/67531/metadc671917

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • December 1, 1995

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • April 7, 2016, 8:20 p.m.

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Atwood, C.L. Modeling patterns in count data using loglinear and related models, report, December 1, 1995; Idaho Falls, Idaho. (digital.library.unt.edu/ark:/67531/metadc671917/: accessed December 15, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.