Hello R-users:
I am using "yags" for fitting GEE which is giving me the same result as "Proc
GENMOD". Now I have couple of questions related to yags output. (By the way,
someone told me to run the geeglm for the same analysis and I did run but did
not get the same result as of genmod and don't know how to correct the geeglm
codes so that all three will be same!)
Questions:
1. How can I get the p-value from yags output ?
2. How can I get the regression coefficients as a seperate row or column vector
from the output for my simulation please? Also, how can I get the standard
errors of these reg. coefficients as a seperate vector? Notice, as it is
highlighted below, beta1=coef(wee) giving me "NULL" and also summary(wee) is
not giving me nothing!
The following is the output from the yags analysis:
> yf=formula(Ddimer~newrace+steroid+treatment+SOFA+PSI)
> wee=yags(yf, id=Subject, data=final, cor.met=as.double(rep(0:6, 872)),
> family=gaussian, corstruct="exchangeable", control=yags.control(), weights=w,
> betainit=NULL, alphainit=.1, subset=NULL)
> wee
YAGS (yet another GEE solver) $Date: 2004/10/22 18:49:23 $
Call:
yags(formula = yf, id = Subject, cor.met = as.double(rep(0:6,
872)), family = gaussian, corstruct = "exchangeable", control =
yags.control(),
weights = w, betainit = NULL, alphainit = 0.1, data = final,
subset = NULL)
Regression estimates:
est. naive s.e. naive z sand. s.e. sand. z
p-value <--How to generate it?
(Intercept) 6.972275093 0.122301393 57.008959 0.321211401 21.7061881 ?
newrace -0.238497110 0.089208731 -2.673473 0.119576217 -1.9945196 ?
steroid -0.464207865 0.063099906 -7.356712 0.194455948 -2.3872135 ?
treatment 0.140764455 0.080611978 1.746198 0.192932560 0.7296045 ?
SOFA -0.025986017 0.014140353 -1.837721 0.048131236 -0.5398992 ?
PSI 0.007095163 0.001035622 6.851114 0.003543198 2.0024740 ?
Working correlation model: exchangeable
alpha est: 0.7344
NULL
Pan QIC(R): 7534.732
QLS: 56989.3
Rotnitzky-Jewell: 9.477, 143.987
yags/R: $Id: yags.R,v 1.5 2004/10/22 18:49:23 stvjc Exp $
> beta1=coef(wee)
> beta1
NULL
> summary(wee)
Length Class Mode
1 yagsResult S4
> summary(wee)
FYI, in the following geeglm analysis, I have gotten beta=coef(wgee) as a row
vector(highlighted):
mf=formula(Ddimer~newrace+steroid+treatment+SOFA+PSI)
> wgee=geeglm(mf, id=Subject, data=na.omit(final), weights=w,
> family=gaussian("identity"), corstr="exchangeable")
> beta=coef(wgee)
> beta
(Intercept) newrace steroid treatment SOFA PSI
6.904767685 -0.228246050 -0.425099489 0.160940654 -0.024995782 0.006562448
> summary(wgee)
Call:
geeglm(formula = mf, family = gaussian("identity"), data = na.omit(final),
weights = w, id = Subject, corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald p(>W)
(Intercept) 6.904767685 0.275425965 628.4755438 0.00000000
newrace -0.228246050 0.110604904 4.2585110 0.03905414
steroid -0.425099489 0.181105281 5.5095856 0.01891253
treatment 0.160940654 0.174823465 0.8474851 0.35726476
SOFA -0.024995782 0.044632439 0.3136406 0.57545474
PSI 0.006562448 0.003313452 3.9225669 0.04764208
If you could help me by answering these questions, I would really appreciate
your help.
Sincere thanks,
Sattar
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