[R-sig-ME] Testing interaction between fixed effect and random effect nested within another random effect
Thierry.ONKELINX at inbo.be
Thu Oct 30 10:10:34 CET 2014
Much depends on how you code Line. If Each line has a unique code, thus each line ID occurs in only one block, then (1|Sex:Block:Line) is equal to (1|Sex:Line). If you have a crossed design and you reuse line ID among block (a line ID can occur in more than one block), then (1|Sex:Block:Line) is different from (1|Sex:Line). (1|Sex:Block:Line) is the most explicit way to write it and it does not depends on the coding of line ID.
A few more things:
- Although block is random from a philosophical standpoint, it is better to use it as a fixed effect because it has only 3 levels. More details on http://glmm.wikidot.com/faq
- I'd rather look at (0 + Sex|Line) than (1|Line:Sex). (0 + Sex|Line) allows for a different variance in line effect between male and female, and a correlation between male and female within the line
M1 <- lmer(FitnessCured ~ Sex + Block + (0 + Sex|Block:Line), noNAdata)
M2 <- lmer(FitnessCured ~ Sex + Block + (1|Block:Line), noNAdata)
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
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Thierry.Onkelinx op inbo.be
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Van: r-sig-mixed-models-bounces op r-project.org [mailto:r-sig-mixed-models-bounces op r-project.org] Namens Eoin Duffy
Verzonden: dinsdag 28 oktober 2014 22:14
Aan: r-sig-mixed-models op r-project.org
Onderwerp: [R-sig-ME] Testing interaction between fixed effect and random effect nested within another random effect
Hello mixed model list
I am working on a mixed model using lmer in R and I am a bit stuck on some coding. I have measured male and female fitness in Drosophila from 35 inbred lines (genotype) over three blocks.
My response variable is 'fitness' with n=10 individuals/sex/line/block tested.
Sex is fixed, Block is random and Line nested within block is random. I primarily interested in the interaction between sex and line. Therefore my model looks like
If I wanted to tested the significance of the Sex:Line interaction my plan is to just compare the above model to a model without the interaction and use anova to compare the two models
However what I am wondering is if I am testing the significance of the Sex:Line interaction (included as a random effect) will R know Line is nested within Block ???
How do I specify the interaction between Sex by Line nested within Block ??
Should it be something like
Any thoughts would be appreciated. I have included a sample of my data below
Block Line Sex FitnessInfected FitnessCured2 1 2 M
1.4573 0.22153 1 2 M 1.1551
1.13794 1 2 M 1.4573 1.13797 1 2
M 1.4573 0.41089 1 2 M -1.5648
1.137911 1 2 F -0.2669 -1.247312 1
2 F 0.2785 -1.247313 1 2 F -0.5396
-1.247314 1 2 F -0.5396 0.460215 1
2 F 1.8237 -1.247316 1 2 F
0.7330 0.496517 1 2 F 1.5511 -1.247318
1 2 F -0.5396 1.477419 1 2 F
1.0966 1.186820 1 2 F -0.5396
-1.247321 1 3 M 1.2054 0.716222 1 3
M 1.2585 0.314624 1 3 M -1.5648
0.267226 1 3 M -0.8932 -0.861527 1
3 M 0.5047 1.137928 1 3 M 0.7704
1.137929 1 3 M -1.5648 -1.768931 1
3 F -0.5396 0.678232 1 3 F
-0.5396 -1.247333 1 3 F -0.5396 1.077834
1 3 F -0.5396 -1.247335 1 3 F
-0.5396 -1.247336 1 3 F -0.5396
0.714537 1 3 F -0.5396 0.7508
Institute of Environmental Sciences
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