Department of Environmental Studies, Emory University, 400 Dowman Drive, Suite E510, Atlanta, GA 30322, USA.
J Med Entomol. 2010 May;47(3):291-8. doi: 10.1603/me09250.
Lack of independence, or pseudoreplication, in samples from ecological studies of insects reflects the complexity of working with living organisms: the finite and limited input of individuals, their relatedness (ecological and/or genetic), and the need to group organisms into functional experimental units to estimate population parameters (e.g., cohort replicates). Several decades ago, when the issue of pseudoreplication was first recognized, it was highlighted that mainstream statistical tools were unable to account for the lack of independence. For example, the variability as a result of differences across individuals would be confounded with that of the experimental units where they were observed (e.g., pans for mosquito larvae), whereas both sources of variability now can be separated using modern statistical techniques, such as the linear mixed effects model, that explicitly consider the different scales of variability in a dataset (e.g., mosquitoes and pans). However, the perception of pseudoreplication as a problem without solution remains. This study presents concepts to critically appraise pseudoreplication and the linear mixed effects model as a statistical solution for analyzing data with pseudoreplication, by separating the different sources of variability and thereby generating correct inferences from data gathered in studies with constraints in randomization.
昆虫生态学研究样本缺乏独立性（或伪重复）反映了与活体生物合作的复杂性：个体的有限和有限投入、它们的亲缘关系（生态和/或遗传），以及将生物体分组为功能实验单位以估计种群参数的需要（例如，群体重复）。几十年前，当首次认识到伪重复问题时，就强调指出主流统计工具无法解释缺乏独立性的问题。例如，由于个体之间的差异而产生的变异性会与观察到它们的实验单位的变异性混淆（例如，蚊子幼虫的盆），而现在可以使用现代统计技术（例如线性混合效应模型）来分离这两个变异性源，该技术明确考虑了数据集不同尺度的变异性（例如，蚊子和盆）。然而，伪重复被认为是一个没有解决方案的问题的看法仍然存在。本研究通过分离不同的变异性源，提出了批判性评估伪重复和线性混合效应模型作为分析具有伪重复数据的统计解决方案的概念，从而从具有随机化限制的研究中收集的数据中得出正确的推论。
