[R-sig-ME] Advice for analysis of biological data - Mixed model or NESTED-Anova?
savani1987 at gmail.com
Thu May 26 11:17:51 CEST 2016
Thanks a lot.
When you say the biggest group. I assume it is just about the number of
animals in the group. Not about about the total number of observations for
And, when I run the code, I get the error
brainmodel<-nlme(logVolume ~ Group , random= ~Group/Animal_ID,
Error in model[][] : object of type 'symbol' is not subsettable
In the full or reduced models with lme4: What might be an reduced model in
Because, in expt design 1 : I only have 3 groups.
On 25 May 2016 at 21:58, Evan Palmer-Young <epalmery at cns.umass.edu> wrote:
> Dear Savani,
> I think you are on the right track. If you use function nlme, you can get
> your p-values straightaway.
> With lme4, you have to employ another function (Likelihood ratio test on
> full and reduced models, or Wald tests with Anova in car) to extract them:
> For your model coding, make sure that the biggest group is listed FIRST.
> So for you:
> model2=lmer(logVolume ~ Group + (1|Animal_ID/Group ),
> data=dat, REML =
> Instead use
> brainmodel<-nlme(logVolume ~ Group , random= ~Group/Animal_ID)
> See some examples under "model specification" on this very helpful page:
> Here are some nlme examples:
> Good luck!
> On Wed, May 25, 2016 at 3:32 PM, Savani Anbalagan <savani1987 at gmail.com>
>> 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
>> 3. I am studying axonal synapses in Brain.
>> 4. I have 3 or more groups (Genotypes: Wild type, Hetero, Homozygous
>> 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
>> 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
>> 10. Some times, we also treat the different groups to a drug. So, it
>> makes another level.
>> 1. > (Imagine a tree with fruits of different sizes. And I am
>> 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
>> 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
>> 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
>> And for experiments with the drug treated vs control.
>> 5. These are the codes that I use to analyze my data: Could you check
>> it is correct?
>> My nested anova code I use:
>> logGFPVol.anova = aov(logVolume ~ Group + Error(Animal_ID/Group),
>> Mixed model code:
>> model2=lmer(logVolume ~ Group + (1|Animal_ID/Group ), data=data, REML =
>> Please feel free to ask if I am unclear.
>> Many thanks,
>> *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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