Analyzing Historical Count Data: Poisson and Negative Binomial Regression Models

Asserts that traditional approaches to multivariate analysis, including standard linear regression techniques, ignore the special character of count data. Explicates three suitable alternatives to standard regression techniques, a simple Poisson regression, a modified Poisson regression, and a negat...

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Bibliographic Details
Published in:Historical methods 1995-06, Vol.28 (3), p.125-131
Main Authors: Beck, E. M., Tolnay, Stewart E.
Format: Article
Language:English
Subjects:
Data Interpretation
Evaluation Criteria
Higher Education
Modified Poisson Regression
Multivariate Analysis
Negative Binomial Model
Probability
Regression (Statistics)
Research Methodology
Research Problems
Social Science Research
Statistical Analysis
Statistical Bias
Statistical Distributions
Statistical Studies
Validity
Citations: Items that this one cites
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Description
Summary:Asserts that traditional approaches to multivariate analysis, including standard linear regression techniques, ignore the special character of count data. Explicates three suitable alternatives to standard regression techniques, a simple Poisson regression, a modified Poisson regression, and a negative binomial model. (MJP)
ISSN:0161-5440
1940-1906
DOI:10.1080/01615440.1995.9956360