Dear all,
I was suggested in the stack exchange.com to consult in this maling list.
I have data from image analysis of zebrafish brain structures. I will
discuss our data below with some analogy to make my explanation clear.
1. Data model: Group>Animal 1..2...3....10>Volume 1..2..3.....1000
2. Data model: Group>Drug treatment..1..2>Animal 1..2...3....10>Volume
1..2..3.....1000
3. I am studying axonal synapses in Brain.
4. I have 3 or more groups (Genotypes: Wild type, Hetero, Homozygous
mutant)
5. Animals are sacrificied to image them.
6. I have 10+ animals from each group.
7. The number and volume of the synapses are variable.
8. Within the group, some animals have 300 synapses, some have 450
synapses.
9. The volume of the synapses range from 0.2 to 50. The histrogram is
highly skewed towards lower values. A log transformation makes it look
more
normal.
10. Some times, we also treat the different groups to a drug. So, it
makes another level.
11.
Analogy:
1. > (Imagine a tree with fruits of different sizes. And I am interested
in the size of the fruits)
2. >(Lets say, I have trees of different species. example Indian Mango
vs Brazilian Mango vs another Mango)
3. >(To collect fruits, The trees are cut. )
4. >(10+ trees in each groups)
5. >(The number of fruits vary depending on tree to tree even within
same group. The size of the fruit varies. There are relatively too many
small fruits).
6. >(Some times, fertilizers are added to tree, and then effect of fruit
count/size is also checked)
My questions:
Could you please let me know,
1. Should I perform Nested ANOVA or Mixed model analysis?
2. If mixed model design, should I run the analysis on log transformed
data or raw data? Is the distribution important for mixed model
analysis?
3. If drug treatment is added, Is it Nested or Mixed model design?
4. For mixed model analysis how can I calculate p-value? Could you
please let me know for both the cases. For experiments, without any
drug.
And for experiments with the drug treated vs control.
5. These are the codes that I use to analyze my data: Could you check if
it is correct?
My nested anova code I use:
logGFPVol.anova = aov(logVolume ~ Group + Error(Animal_ID/Group),
data=data)
summary(logGFPHBVol.anova)
Mixed model code:
model2=lmer(logVolume ~ Group + (1|Animal_ID/Group ), data=data, REML =
FALSE)
summary(model2)
Please feel free to ask if I am unclear.
Many thanks,
Savani
--------------------------------------------------------
*Savani Anbalagan, Ph.D*
*Dept. of Mol. Cell Biology*
*Weizmann Institute of Science234 Herzl St., Rehovot 76100,*
*ISRAELPhone: +972-8934-6158*
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