Dear All,
I am estimating a Cox proportional hazard model, with several interactions
of the type a*z + a*y + a*x + b*z + b*y + b*x.
I need to know if the first three (the "a"s) are jointly significantly
different from the last three (the "b"s). I have tried several approaches,
but have been unsuccessful.
Here's the model, and the code I came up with, with the obvious
shortcomings.
modelPG2 <- coxph(Surv(t0, t, d) ~ civilian + monarch + txmonarch
+ civwar + lngdpcap + growth
+ tropen4 + dopen4
+ lnpop
+ age0 + entry1 + powtimes
+ initiator2 + defender2 + inherit
+ milwinsh + millosesh + mildrawsh +
milwinwar + millosewar + mildrawwar
+ civwinsh + civlosesh + civdrawsh +
civwinwar + civlosewar + civdrawwar
+ monwinsh + monlosesh + mondrawsh +
monwinwar + monlosewar + mondrawwar
+ frailty(ccode), na.action=na.exclude,
data=LeaderPG.data,
control=coxph.control(eps=1e-09,iter.max=100,outer.max=100))
library(aod)
# To test if Military Leaders are equally sensitive to the outcome of WAR
as Civilian leaders we need a JOINT test.
wald.test(b=coef(modelPG2), Sigma = vcov(modelPG2), Terms= c(19:21),
H0=c(-2.9101, 2.4028, -1.6504))
#wald.test(b=coef(modelPG2), Sigma = vcov(modelPG2), Terms= c(19:21),
H0=c(0, 2.4028, 0))
wald.test(b=coef(modelPG2), Sigma = vcov(modelPG2), Terms= c(25:27),
H0=c(-8.2330,2.3041,-0.2626))
Any help would be very much appreciated.
Hein Goemans.
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