I am a biologist and am attempting to analyze the effects of time and location on depth. I was told I needed to use a mixed effects model to account for the random variables of Individual and tracking type, but am unfamiliar with the outputs and am having difficulty interpreting it. I am not sure if there is something wrong with my model, or if I do not correctly understand how to read the output.
I am attempting to analyze data that looks like this:
Name Seconds Depth Time Location Place Tracking 8601 29422 19 Day Off Hawaii Active 8601 29434 29 Day Off Hawaii Active 8601 29444 36 Day Off Hawaii Active 8601 29455 44 Day Off Hawaii Active 8601 29466 50 Day Off Hawaii Active 8601 29480 55 Day Off Hawaii Active
and I built a model using R package
lmer. My model is
Fixed effects: Estimate Std. Error t value (Intercept) 28.577 4.263 6.703 TimeNight 26.021 6.341 4.104 LocationOn -22.835 1.181 -19.327 TimeNight:LocationOn -33.049 1.567 -21.088
Systematically removing terms revealed that
Time, and their interaction were all significant.
I am mostly interested in the differences between
On/Day, as well as
Off/Day. I know that
Off/Day is 28.577, with
Off/Night at (28.577+26.021), and
On/Day at (28.577-22.835). My trouble comes in interpreting
Night/On, since the answer cannot be negative (can't have negative depth). Does the negative value mean this type of model isn't appropriate for my situation?
Also, is there a way to determine if the values for
On/Night are significantly different from
On/Day? Can I use a