I have the following experimental layout:

1. five different treatments - harvesting rates, ranging from 0 to 1, indicating proportion of branches per plant harvested

2. 75 plants, randomly assigned plants to each treatment, resulting in 15 plants per treatment

3. followed over 5 years, resulting in five data points per individual plant

Now I want to analyse the data, and see if the treatment (harvesting rate) has an impact on different measured variables (height of plant, cumulative number of stems harvested, ...), preferably also in which years they differ.

Initially I thought using a repeated-measures ANOVA, but the subjects per treatment are different, but they are followed over time, which violates independence assumptions of normal ANOVAs. So which statistic test can I use here?

I use R, so an example in R would be nice.

Thanks,

Rainer

I have the following experimental layout:

1. five different treatments - harvesting rates, ranging from 0 to 1, indicating proportion of branches per plant harvested

2. 75 plants, randomly assigned plants to each treatment, resulting in 15 plants per treatment

3. followed over 5 years, resulting in five data points per individual plant

Now I want to analyse the data and see if the treatment (harvesting rate) has an impact on different measured variables (e.g., height of plant, cumulative number of stems harvested), and preferably also in which years they differ.

Initially I thought using a repeated-measures ANOVA, but the subjects per treatment are different, but they are followed over time, which violates independence assumptions of normal ANOVAs. So which statistical test can I use here?

I use R, so an example in R would be nice.