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4 messages · Ashta, Henrique Dallazuanna, Adaikalavan Ramasamy

#
Hi all,
I am trying to interparete  the result of the following output from  lm;


fit1 =lm(Feed _Intake ~ weight + season + weight*season)
Season has three classes(x,y,z)

Reults are

Estimate (Intercept)               21.51559
weight                                       2.13051
factor(season)y                      10.59739
factor(season)z                        1.30421
weight:factor(season)y          10.1
weight:factor(season)z          21.70288

My question are  what is the estimate of season x?

Could it be possible to change the output in the following way?

factor(season)x
factor(season)y
weight:factor(season)x
weight:factor(season)y

Thanks in adavance
#
Try this:

DF$season <- relevel(DF$season, 'y')
fit1 <- lm(Feed_Intake ~ weight + season + weight*season, data = DF)
On Mon, Jan 18, 2010 at 2:00 PM, Ashta <sewashm at gmail.com> wrote:

  
    
#
Season X is taken as the reference category. So the output 
"factor(season)y   10.59739" means the feed_intake is higher by 10.59 
units in Season Y _compared to_ Season X.

Change your levels in season. E.g.
   season <- factor(season, levels=c("Z", "X", "Y")
which means that Z will be taken as the reference category. Also read 
help(contrasts).

Regards, Adai
Ashta wrote:
#
Hi all,

I have a data set  such that  the response variable size  binary (Short or Long)
Color has two classes (red and green)  red=1 ; green=0
Lm1 <- glm(size ~color, data =test, family = binomial())
                   Estimate   Std. Error    z value
(Intercept)  12.052    3.11037    -12.273
color              0.7850    0.06624   3.952
How do I get the probability of sizes for the two different colors(red
and green)?
On Mon, Jan 18, 2010 at 11:15 AM, Henrique Dallazuanna <wwwhsd at gmail.com> wrote: