Hi
I'm having some difficulty understanding my output (below) from GEE. the
person who wrote the program included some comments about the '3-th term
gives diff between hyp/ox at time..', and after created an L vector to use
for a WALD test. I was wondering if someone could help me understand the
GEE output, the programmers comment, how L was determined, and its use in
the WALD test. I have tried looking online but unfortunatly have had no
luck.
Thank you so much!
fit=gee(foci~as.factor(time)*cond,id=exper,data=drt,family=poisson(link
"log"))
Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27
running glm to get initial regression estimate
(Intercept) as.factor(time)24
3.051177 -2.705675
condHypoxia as.factor(time)24:condHypoxia
-0.402259
1.429034> pv=2*(1-pnorm(abs(summary(fit)$coef[,5])))
> data.frame(summary(fit)$coef,pv)
Estimate Naive.S.E. Naive.z Robust.S.E.
(Intercept) 3.051177 0.02221052 137.37527 0.04897055
as.factor(time)24 -2.705675 0.10890056 -24.84537 0.19987174
condHypoxia -0.402259 0.03907961 -10.29332 0.10661248
as.factor(time)24:condHypoxia 1.429034 0.12549576 11.38711 0.17867421
Robust.z pv
(Intercept) 62.306363 0.000000e+00
as.factor(time)24 -13.537057 0.000000e+00
condHypoxia -3.773095 1.612350e-04
as.factor(time)24:condHypoxia 7.997988 1.332268e-15> ftable(table(drt$cond,drt$time,predict(fit)))
0.345501643340608 1.37227675004058 2.64891772174934
3.05117673373261
Oxia 0.5 0 0
0 485
24 315 0
0 0
Hypoxia 0.5 0 0
346 0
24 0 449
0 0> ## 3-th term gives the difference between the Hypoxia/Oxia at time=0.5
> ## the difference between Hypoxia/Oxia at time=24
> L=matrix(c(0,0,1,1),nrow=1)
> fit$coef[L==1]
condHypoxia as.factor(time)24:condHypoxia
-0.402259
1.429034> L%*%fit$coef
[,1]
[1,] 1.026775>
>
> wald.test(fit$robust.variance,fit$coef,L=L)
Wald test:
----------
Chi-squared test:
X2 = 23.8, df = 1, P(> X2) = 1.1e-06
[[alternative HTML version deleted]]
