@article{ref1,
title="Pick your poisson: a tutorial on analyzing counts of student victimization data",
journal="Journal of school violence",
year="2012",
author="Huang, Francis L. and Cornell, Dewey G.",
volume="11",
number="3",
pages="187-206",
abstract="School violence research is often concerned with infrequently occurring events such as counts of the number of bullying incidents or fights a student may experience. Analyzing count data using ordinary least squares regression may produce improbable predicted values, and as a result of regression assumption violations, result in higher Type I errors. Count data are optimally analyzed using Poisson-based regression techniques such as Poisson or negative binomial regression. We apply these techniques to an example study of bullying in a statewide sample of 290 high schools and explain how Poisson-based analyses, although less familiar to many researchers, can produce findings that are more accurate and reliable, and are easier to interpret in real-world contexts.<p /><p>Language: en</p>",
language="en",
issn="1538-8220",
doi="10.1080/15388220.2012.682010",
url="http://dx.doi.org/10.1080/15388220.2012.682010"
}