Which model/statistical test should I use?

[YolineVDE]

Hi,

Soon I will be performing an experiment where I must grow 4 different plant species under 4 different stressors, each stressor containing 4 levels of 'severity' of the stressor or in other words a difference in concentration. Growth of the plants will be measured over 22 time points, but all these time points will be reduced to a single value per plant, showing the overall growth of the plant over the course of the experiment.

So each observation contains the following data:

• 1 value giving its growth (continuous variable)
• 1 value giving the plant species (discrete variable)
• 1 value for the stressor (type of stressor) (discrete variable)
• 1 value for the gradient step of the stressor (discrete variable, but different values for all different stressors)

How should I model this or what statistical test is appropriate for this type of design? In short, I want to check the effect of two discrete variables (plant species and stressor type) on a continuous variable (plant growth), but within one of the two discrete variables (type of stressor), another variable is nested, namely the gradient steps of that stressor. I haven't found any type of ANOVA or lm that tackles this problem.

Thanks in advance!

 

[Miner]

You have two initial factors (plant species, stressor type). However, the levels (stressor gradient) are nested within stressor type. Therefore this becomes a third, nested factor. In addition, you have repeated measures (growth over time). You should be able to analyze this as a repeated measures, nested ANOVA or as a repeated measures GLM with a nested factor.