Dear S-plus experts,
I have a linear model where the response variable is survival. My focal
explanatory variable is body mass, but I also include the time of the
season (day.number) in the model. There is a significant interaction
between the two continuous variables.
model <- lm(survival ~ mass * day.number)
The coefficients:
mass: -0.05
day.number: -0.051
mass*day.number: 0.014
From what I have heard and partly read, I have got the impression
(well founded or not...?) that it is difficult to interpret the
coefficients in an interaction between continuous terms. My very naive
and entirely qualitative interpretation of the above results would be:
There is a negative effect of mass on survival early in the season (low
day.number). However as the season proceeds the positive interaction,
mass*day.number, cancels the negative effect of mass. Is this correct?
How do I calculate the actual value of survival for a given mass and
day.number?
Can anyone please help me with a convenient way to represent the
interaction graphically in S-plus and to interpret the coefficients
quantitatively (analoguous to an interaction with a factor).
Thanks a lot in advance for any kinds of suggestions!
Sincerely,
Henrik Pärn
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