Hi All,
I have a dataset which contains 4 variables: area, group, time, y,
Area is a factor that has two levels A and B, group is a factor that is
nested within area. There are four groups within each area.
y is the response variable, and time refers to different days.
Below is the how data looks like.
First, I fit separate ancova for each area (area A and B), For each area,
I obtained different regression lines for each group within that area.
mod1 <- lm(y ~ month * group, data=two[two$area=="A"]
mod2 <- lm(y ~ month * group, data=two[two$area=="B"]
I want to fit the model at one time by using the nested structure
mod3 <- lm(y ~ -1+ month * (area/group), data=two)
I get different results using mod 3 from using mod1 and mod2.
Can someone give some suggestion on this. How can I specify the model in
R to simultaneously fit the model to get the same results as from mod1 and
mod2.
Thanks very much!
Hanna
> head(two[two$area=="A",]) group time y area
79 1 3 -1.394327 A
80 1 6 -1.435485 A
81 1 9 -1.406497 A
82 1 12 -1.265848 A
83 1 0 -1.316768 A
84 1 6 -1.431292 A> head(two[two$area=="B",]) group time
y area
1 1 0 -2.145581 B
2 1 0 -1.910543 B
3 1 0 -2.128632 B
4 1 3 -2.079442 B
5 1 3 -2.273026 B
6 1 6 -2.312635 B
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