Joint test

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]

Behalf Of Hein Goemans
Sent: February-06-09 3:30 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Joint test

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.