Hi, 
I have longitudinal data corresponding to different indicators about
fishing activities by vessel. I used package lme4 to estimate the mixed model. 

LMM1 <- lmer(Op_Obj ~ YEAR
+ (1 + YEAR| fBOAT), data=YM, family=gaussian, na.action=na.omit, verbose=T)

I saw that
analyzing longitudinal data, individuals (vessels in my case) correspond to
random effects, while time variable are fixed effects. At the end I will have
the random effects coefficients of each individual and correlated intercept.
But I am interested in variation among years instead among vessels. So I put
the time in random effects and vessels as fixed effects. Is this valid? I mean,
what happen with the independency of the data?

LMM2 <- lmer(Op_Obj ~ BOAT
+ (1 + BOAT | fYEAR), data=YM, family=gaussian, na.action=na.omit, verbose=T)

At the end,
I would like to use the random effects coefficients to use a Bayesian Change Point
analysis to try to find sudden changes in each indicator that I used.

Thanks a
lot!
EDGAR
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