Negative Binomial regression is a staple in Operations Management empirical research. Most of its analytical aspects are considered either self-evident, or minutiae that are better left to specialised textbooks. But what if the evidence provided by trusted sources disagrees? In this note I set out to verify results about the Negative Binomial regression specification presented in widely-cited academic sources. I identify problems in how these sources approach the gamma function and its derivatives, with repercussions on the Fisher Information Matrix that may ultimately affect statistical testing. By elevating computations that are rarely specified in full, I provide recommendations to improve methodological evidence that is typically presented without proof.

翻译：负二项回归是运营管理实证研究中的基础方法。其多数分析特性常被视为不言自明，或是更适合专业教材探讨的细节。但当可信来源提供的证据相互矛盾时该如何应对？本文旨在验证广泛引用的学术文献中关于负二项回归设定的结果。我发现这些文献在处理伽玛函数及其导数时存在问题，这些问题可能影响费希尔信息矩阵，并最终波及统计检验。通过详细阐述通常未被完整说明的计算过程，本文为改进通常未经证明的方法论证据提供了建议。