Weng Hsin-Yi, Messam Locksley L McV
Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, USA.
Section: Herd Health and Animal Husbandry, School of Veterinary Medicine, University College Dublin, Dublin, Ireland.
J Vet Intern Med. 2025 Jan-Feb;39(1):e17258. doi: 10.1111/jvim.17258. Epub 2024 Dec 2.
Understanding and correctly interpreting statistical results presented in scientific articles is a required skill for practicing evidence-based veterinary medicine. A prerequisite for doing so is the adequate reporting of the results in scientific journals. However, most authors of veterinary publications determine the importance of their findings based on statistical significance (ie, P < .05), indicating that neither the limitations of using P values for inference nor the existence of more appropriate alternatives are widely appreciated in veterinary medicine. This deficiency in knowledge indicates a need to increase awareness in veterinary medicine regarding reporting statistical measures that quantify the magnitude of an effect along with its level of uncertainty, and then interpreting these results for clinical decision making. We utilize a hypothetical randomized controlled trial of dietary management in cats with chronic kidney disease to discuss some common misconceptions about P values and provide practical suggestions for alternatives. Reporting appropriate effect estimates along with their confidence intervals will allow veterinarians to easily and correctly determine whether the magnitude of the effect of interest meets clinical needs while acknowledging uncertainty in the results. We also describe confidence interval functions and show their utility as visual tools in aiding interpretation of confidence intervals. By providing practical guidance, we show that a change in reporting and interpreting statistical results is feasible and necessary. We hope this crucial step will promote clinical decision making based on effect estimates and confidence intervals.
理解并正确解读科学文章中呈现的统计结果是实施循证兽医学所需的一项技能。这样做的一个先决条件是科学期刊对结果进行充分报告。然而,大多数兽医出版物的作者根据统计学显著性(即P < .05)来确定其研究结果的重要性,这表明在兽医学中,使用P值进行推断的局限性以及更合适替代方法的存在并未得到广泛认可。这种知识上的欠缺表明有必要提高兽医学领域对报告统计量度的认识,这些统计量度既能量化效应的大小,又能体现其不确定性水平,然后为临床决策解读这些结果。我们利用一项关于慢性肾病猫饮食管理的假设性随机对照试验来讨论一些关于P值的常见误解,并提供替代方法的实用建议。报告适当的效应估计值及其置信区间将使兽医能够轻松且正确地确定感兴趣的效应大小是否满足临床需求,同时承认结果存在不确定性。我们还描述了置信区间函数,并展示了它们作为辅助解读置信区间的可视化工具的效用。通过提供实用指导,我们表明改变报告和解读统计结果是可行且必要的。我们希望这一关键步骤将促进基于效应估计值和置信区间的临床决策。