Thanks for the response. It is actually a repeated measures study, I
just mention the fixed effects specification because I think I know the
random effect specification, i.e.:
Random = ~ 1|subject
And thanks for the tip about the nonlinear model and the S-plus list. I
will check out nlme and the other list.
Eric
On 6/9/05, Eric Hack [EMAIL PROTECTED] wrote:
Dear All,
I am trying to specify the following fixed effects model for lme:
If you have a linear fixed-effects model you should use lm, not lme.
y ~ constant1 - beta1*(x - beta2)
where y is the response, x is the independent variable, and the
operators above are real arithmetic operations of addition,
subtraction,
and multiplication. I realize that this model is just a
reparameterization of y=beta0+beta1*x, but I am using this
parameterization because I am specifically interested in confidence
bounds for beta2.
You would need to fit that as a nonlinear model. In reference to such
models linear means linear in the parameters and that model isn't.
I have looked at the help, but the closest hint I find is the I()
function, and that does not seem to work this way.
I confess that I am actually using S-plus, but there does not seem to
be
a resource like this list for S-plus.
Look for the S-news email list (http://www.biostat.wustl.edu/s-news/)
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