I have conducted a repeated-measures ANOVA and a Tukey post hoc test. The data I have is for 3 seedling mutant lines, I am comparing their root growth over a timecourse of 19 hours. Within each group, there are 35 seedlings measured at each time point. The Tukey test gives an indication of significance between the seedling lines, however does not show at what time this significance occurs, therefore I have been trying to find this out using a one-way ANOVA at each time point, which doesn't make sense as each seedling is repeatedly measured.
make interaction between "3 seedling mutant lines" with time (including time levels, for example 1, 2, 3, ... etc.)
With the model construct it is difficult to answer your question. What does you variance model look like? What is defined as fixed, subject and time steps. That would help provide insightful answers. Good luck.
It's fine to do that at each time point as long as there is replication. So you compare the means of the 35 at your chosen time points. Or you could graphically display the data, which would show you too
make interaction between "3 seedling mutant lines" with time (including time levels, for example 1, 2, 3, ... etc.)
I also agree with Andrew Paul McKenzie Pegman. I also faced a similar situation and then I analyzed data using ANOVA at each and every time step separately. In repeated measure ANOVA, another disadvantage I noticed was a lot of valuable data were not taken into consideration if missing values were present too.
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