I ran an experiment where subjects exercised in different climatic conditions. The response variable is the subjects' internal (core) temperatures.
There were 30 subjects and some participated in more than one trial. Each trial had a different ambient temperature, relative humidity, etc. Because of the non-independence of some of the subjects' data due to participating more than once, I decided to use a linear mixed effects model with Subject as the random effect. I also think I need to nest Subject within Trial due to the fact that different climatic conditions effect the subjects' temperatures.
The response variable is the subjects' temperatures and the fixed effects are the subjects' mass, age, and body fat percentage.
Here is my model, in package lme4 in R:
>mod=lmer(Temp ~ Mass + Age + Fat + (1|Subject/Trial), data=data, REML=FALSE)
I get the error:
Error: number of levels of each grouping factor must be < number of observations
I have 43 observations and 6 different trials. Does this mean I just didn't collect enough data to be able to fit this model? Or is there another explanation/anything I can do?