[R-sig-ME] including the same variable both as fixed and as part of a complex random variable?

[Hans Ekbrand]

Dear list followers,

I am wondering wheter I should include some variables both as fixed
and as parts of complex random terms, and I hope you can give some
guidance.

Are the "real" differences between be models below? If so, what are
the differences?

I have used the variables labour.market.position and country in the
exampels below, but the question is of course a general one.

fit.1 <- glmer(poverty.third.year ~ 1 + (0 + labour.market.position | country) +
               gender, family = binomial("logit"), data = poverty.risks)

fit.2 <- glmer(poverty.third.year ~ 1 + labour.market.position + (0 + labour.market.position | country) + 
                gender, family = binomial("logit"), data = poverty.risks)

fit.3 <- glmer(poverty.third.year ~ 1 + labour.market.position + (1 | country) + (0 + labour.market.position | country) +
             gender, family = binomial("logit"), data = poverty.risks)

If there are no "real" differences between these, then which do you
prefer, and why?

-- 
Hans Ekbrand