Dear Hein,
I'm not entirely sure that I understand what you want to do, but I think
that you want to test that the coefficient of milwinwar equals that of
civwinwar, and similarly and simultaneously for two other pairs of
coefficients. If so, you should be able to use the linear.hypothesis()
function in the car package:
linear.hypothesis(modelPG2, c("milwinwar = civwinwar", "millosewar =
civlosewar", "mildrawwar = civdrawwar"))
You should be able to get the same test from the wald.test() function that
you tried, but I believe that you would have to build the hypothesis matrix
manually.
I hope this helps,
John
------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On
> Behalf Of Hein Goemans
> Sent: February-06-09 3:30 PM
> To: r-h...@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.
>
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