Improved two-step analysis of germination data from complex experimental designs
| Autor: | Signe Marie Jensen, Jens C. Streibig, Eshagh Keshtkar, Christian Ritz, Dustin Wolkis |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Computer science Design of experiments Carry (arithmetic) Two step 04 agricultural and veterinary sciences Plant Science Factorial experiment 01 natural sciences Visualization Replication (statistics) 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Statistical analysis Algorithm 010606 plant biology & botany |
| Zdroj: | Seed Science Research. 30:194-198 |
| ISSN: | 1475-2735 0960-2585 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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