Germination experiments are becoming increasingly complex and they are now routinely involving several experimental factors. Recently, a two-step approach utilizing meta-analysis methodology has been proposed for the estimation of hierarchical models suitable for describing data from such complex experiments. Step 1 involves fitting models to data from each sub-experiment, whereas Step 2 involves combination estimates from all model fits obtained in Step 1. However, one shortcoming of this approach was that visualization of resulting fitted germination curves was difficult. Here, we describe in detail an improved two-step analysis that allows visualization of cumulated data together with fitted curves and confidence bands. Also, we demonstrate in detail, through two examples, how to carry out the statistical analysis in practice.

中文翻译：

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改进了对来自复杂实验设计的发芽数据的两步分析

发芽实验变得越来越复杂，现在它们通常涉及几个实验因素。最近，已经提出了一种利用元分析方法的两步方法，用于估计适合描述来自此类复杂实验的数据的分层模型。第 1 步涉及对来自每个子实验的数据进行模型拟合，而第 2 步涉及对第 1 步中获得的所有模型拟合的组合估计。然而，这种方法的一个缺点是很难对生成的拟合发芽曲线进行可视化。在这里，我们详细描述了一种改进的两步分析，它允许将累积数据与拟合曲线和置信带一起可视化。此外，我们通过两个例子详细演示了如何在实践中进行统计分析。