extract variables from linear model

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extract variables from linear model

Jörg Schaber

I fitted a mixed linear model y = a + b + a*b + c + error, with c being
the random factor:
lmefit <- lme(y ~ a * b - 1 , random = ~ 1 | c, na.action='na.omit')

Is there a way to omit some level combinations of the cross-term a:b?
E.g. those that are not significant?

When I add the coefficients of a, b and a:b to get the combined effect
without the effect of c, do then the standard errors of the coefficients
also add?



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