Luciano Alison, Churchill Gary A
The Jackson Laboratory, Bar Harbor, ME, USA.
bioRxiv. 2024 Aug 7:2024.08.06.606373. doi: 10.1101/2024.08.06.606373.
Analysis of preclinical lifespan studies often assume that outcome data from co-housed animals are independent. In practice, treatments, such as controlled feeding or putative life-extending compounds, are applied to whole housing units, and as a result the outcomes are potentially correlated within housing units. We consider intra-class (here, intra-cage) correlation in three published and two unpublished lifespan studies of aged mice encompassing more than 20 thousand observations. We show that the independence assumption underlying common analytic techniques does not hold in these data, particularly for traits associated with frailty. We describe and demonstrate various analytical tools available to accommodate this study design and highlight a limitation of standard variance components models (i.e., linear mixed models) which are the usual statistical tool for handling correlated errors. Through simulations, we examine the statistical biases resulting from intra-cage correlations with similar magnitudes as observed in these case studies and discuss implications for power and reproducibility.
临床前寿命研究的分析通常假定同笼饲养动物的结果数据是独立的。实际上，诸如控制饮食或假定的寿命延长化合物等处理是应用于整个饲养单元的，因此结果在饲养单元内可能存在相关性。我们在三项已发表和两项未发表的老年小鼠寿命研究中考虑了组内（此处为笼内）相关性，这些研究包含了超过两万条观测数据。我们表明，常见分析技术所依据的独立性假设在这些数据中并不成立，尤其是对于与虚弱相关的性状。我们描述并演示了可用于适应这种研究设计的各种分析工具，并强调了标准方差成分模型（即线性混合模型）的一个局限性，该模型是处理相关误差的常用统计工具。通过模拟，我们研究了笼内相关性导致的统计偏差，其大小与这些案例研究中观察到的相似，并讨论了对检验效能和可重复性的影响。
