#3212. Treatment effects on count outcomes with non-normal covariates

September 2026publication date
Proposal available till 12-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Statistics and Probability;
Arts and Humanities (miscellaneous);
Psychology (all);
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Abstract:
When controlling for additional covariates, a negative binomial regression model is usually applied to estimate conditional expectations of the count outcome. The moment-based approach makes it possible to control for multivariate normally distributed covariates and provides more reliable inferences under certain conditions. The research provides three different ways to account for non-normally distributed continuous covariates in this approach: an alternative, known non-normal distribution; a plausible factorization of the joint distribution; and an approximation using finite Gaussian mixtures. A saturated model is used for categorical covariates, making a distributional assumption obsolete.
Keywords:
negative binomial regression; non-normal covariates; treatment effects

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