I have a data set containing root, shoot and seedling growth measurements from 5 treatment groups (at different concentrations, 3 replicates) including control. There were no separate control groups for each treatment group. I have the following doubts (The code for analysis is given below, the data set is attached):

1) SHOULD I PERFORM ONE-WAY ANOVA AND POST HOC ON THE SAME TRANSFORMED DATA SET (IF FITTED WELL)

2) CAN I BELIEVE WHAT I HAVE DONE IN TRIAL 2 IS CORRECT?

3) CAN WE JUSTIFY RUNNING SUCH ANOVA WITH DATA SET CONTAINING ONLY ONE CONTROL FOR ALL THE TREATMENT GROUPS WITH MULTIPLE LEVELS (WITH DIFFERENT CONCENTRATIONS FOR EACH TREATMENT)?

4) CAN I CONSIDER VARIABLES ("ROOT", "SHOOT", "SEEDLING") A THIRD FACTOR (AS THEY REPRESENT DIFFERENT RESPONSES RECEIVING SAME TREATMENTS)?

TRIAL 1)

Two-way anova between concentration and treatment 

md2$concm1

shapiro.test(resid(m1)) ## assumption violated

However I continued ANOVA on log-transformed data as follows:

aov(log(length+1)~conc*treat,data=md2)->m1

shapiro.test(resid(m1))## assumption violated.

TRIAL 2)

Then I split the data and repeated one-way ANOVA with the subset of data with control and each treatment separately

as follows:

rbind(md2[md2$treat=="control"&md2$variable=="root",],md2[md2$treat=="t1"&md2$variable=="root",])->t1

rbind(md2[md2$treat=="control"&md2$variable=="root",],md2[md2$treat=="t2"&md2$variable=="root",])->t2

rbind(md2[md2$treat=="control"&md2$variable=="root",],md2[md2$treat=="t3"&md2$variable=="root",])->t3

rbind(md2[md2$treat=="control"&md2$variable=="root",],md2[md2$treat=="t4"&md2$variable=="root",])->t4

md2$concm1

shapiro.test(resid(m1)) ## assumption not violated

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