Dear list

 

I'm trying to model fish data with a gaussian distribution for prey reactive
distance obtained in lab experiments. Each experimental trial consisted of
giving 1 prey to fish every x min., for a total of 20 prey, and measuring
the reactive distance of fish to the prey. My explanatory variables are
current velocity (0, 8, 12, 26 cm/s), fish size (small, medium and large),
density (2, 4 and 6 fish), trial and fish.id, and I did 3 replicates of each
trial, using each fish only once. Because not all fish reacted to the prey,
the number of reactive distances is not the same for each fish, and hence
not the same for each trial. I wonder whether with this experimental design
I can consider fish.ID and trial as random effects and treat the other
variables as fixed effects. 

 

I’m using lme4 and tried:

 

model<-lmer(reactive.dist~velocity+density+(1|trial/fish.id),family=gaussian
)

 

but got this error and warning:

 

Error: length(f1) == length(f2) is not TRUE

In addition: Warning messages:

1: In fish.id:trial :

  numerical expression has 2518 elements: only the first used

2: In fish.id:trial :

  numerical expression has 2518 elements: only the first used

 

Is this because I don’t have the same number of reactive distances per fish?


 

When I do:

model<-lmer(reactive.dist~velocity+density(1|fish.id),family=gaussian)

it works fine…….

Any suggestions would be greatly appreciated! 

The best

Joana

 

Joana Martelo, PhD Student

Centro de Biologia Ambiental

Departamento de Biologia Animal

Faculdade de Ciências, Edificio C2,5ºPiso,Sala 2.5.15B

1749-016 Lisboa, Portugal

http://ffishgul.fc.ul.pt 

 

 


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