Enquiry about 2nd-order interactions survival analysis
David's answers were correct. You are looking deep into the code when
there is no reason to to so.
1. h(t|(X=x,Z=z)) = exp(Beta0 + XZBeta1)
Most statisticians will tell you that this is an unwise model. The
reason is that if you replace X with "X+1" the fit changes, which is
almost never desirable. What if someone coded your dummy variable as
1/0 instead of 0/1 -- wouldn't you want to get the same fit
Therefore the default in R for the model
lm(y ~ x*z)
is to fit y = b0 + b1 x + b2 z + b3 xz
You can get exactly the model you specify as lm(y ~ x:z), or as
temp <- x*z; lm(y ~ temp)
Statistically, this is almost surely a mistake.
2. The model formulas work across packages. I used lm() above, but
survreg is no different. Formula processing is done by the
model.matrix() function, which survreg, lm, glm, .... all call. My C
code is all downstream of this, and irrelevant to your question.
Terry T
On Sun, 2011-11-13 at 14:39 +0800, Kenji Ryusuke wrote:
Dr Terry Therneau,
Firstly I do apologize upon unsolicited email. I know about Dr Terry
through R package "survival" and alot of your papers.
As we know Equation(1) is a normal parametric survival analysis, I'ld
like to modify it to be a 2nd-order interactions as in Equation(2) :-
h(t|X=x) = exp(Beta0 + XBeta1) ------- (1)
h(t|(X=x,Z=z)) = exp(Beta0 + XZBeta1) ------ (2)
Where x and z are two covariates:
x = dummy variable (1 or 0)
z = factors (people name)
I would like to modify survreg() to be a second-order interactions
regression while there is no 2nd-order interactions survival
regression as I searched over www.rseek.org. I tried to read through
the codes of survreg(), but I am stuck (cannot understand) at
survreg6.c
survreg6.c apply C Language which involves Cholesky decomposition
multi-matrix (first-order interactions) calculation.
1) chinv2.c
2) cholesky3.c
3) chsolve2.c (only solve the equations of first-order interactions)
I do appreciate if Dr Terry willing to enlighten me.
Thank you.
Best,
Ryusuke