The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives

By Stefany Coxe, S. West, L. Aiken. Journal of Personality Assessment, 2009

1,126 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/07279174a35cd895a89341c42ce6d2826d42fee1

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In Experimental and Cognitive Psychology

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Citations in the corpus

The effect of institutional ownership on firm innovation: Evidence from Chinese listed firms (2017, background): “Our OLS specification is valid since the mean of the outcome variable is very close to 10, a benchmark proposed by Coxe et al. (2009).”
All better than being disengaged: Student engagement patterns and their relations to academic self-concept and achievement (2020, background): “The counts of hand-raising deviated from a normal distribution and followed a Poisson distribution (Coxe et al. 2009).”
The effects of personality traits, self-esteem, loneliness, and narcissism on Facebook use among university students (2012, methodology): “Therefore, the current study will use an alternative to the Poisson regression called Negative Binomial regression, which accounts for overdispersion by allowing unexplained variability among individuals (see Coxe et al., 2009).”
Analysis of Machine Learning Techniques for Heart Failure Readmissions (2016, methodology): “In this study, we tested whether these ML approaches could predict readmissions for heart failure more effectively than traditional approaches using logistic regression (LR).(7,9,27,28) We tested these strategies using data that included detailed clinical and sociodemographic information collected d”
A motivational hierarchy within: primacy of the individual self, relational self, or collective self? (2012, methodology): “We tested hypotheses in PROC GENMOD of SAS using a generalized linear model with a Poisson distribution, type 3 simultaneous generalized estimating equations, and an unstructured variance–covariance matrix (Coxe et al., 2009; McCullagh & Nelder, 1989).”
Exploring Identity-Safety Cues and Allyship Among Black Women Students in STEM Environments (2019, methodology): “All the initial models we ran showed a significant overdispersion (i.e., all the models had greater variability than expected for a standard Poisson regression or j ¼ w2Pearson=df is greater than 1; Coxe et al., 2009).”