Re: [R] Survreg function for loglogistic hazard estimation
I a trying to use survreg to fit a Weibull distribution. From the last few messages I understand how to interpret the parameters. However, how do I get the covariance of lambda and alpha? Is there a predict command for that? Thanks -- View this message in context: http://n4.nabble.com/Survreg-function-for-loglogistic-hazard-estimation-tp893503p1604918.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Survreg function for loglogistic hazard estimation
---begin included message -- I am trying to use R to do loglogistic hazard estimation. My plan is to generate a loglogistic hazard sample data and then use survreg to estimate it. If everything is correct, survreg should return the parameters I have used to generate the sample data. I have written the following code to do a time invariant hazard estimation. The output of summary(modloglog) shows the factor loading of dfico is -0.002 instead of 0.005. Also I can not find the survreg's output of alpha and beta of loglogistic regression. Any comments? Thanks a lot, ... -end inclusion -- The survreg function uses the location-scale parameterizations found in Kalbfleisch and Prentice's book The statistical analysis of failure time data. Looking at your code, you are using something different You KP 1/a lambda b gamma And from KP: lambda = exp(-alpha), gamma= 1/sigma, where alpha = linear predictor from the fit sigma = scale factor from the fit I would suggest checking out a copy of the book to verify the above. Second, your method of constructing a random time from the distribution is a mystery to me. I believe your code is equivalent to y - min(which(runif(n) constant)) for any given y (with changing values of the constant). This is a value from the geometic distribution. Terry Therneau __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Survreg function for loglogistic hazard estimation
Dear Terry, Thanks a lot for your reply. The result of survreg reads like: Call: survreg(formula = Surv(end, status) ~ fico_demean, data = raw, dist = loglogistic, model = TRUE) Value Std. Error z p (Intercept) 2.98365 1.34e-03 2233.2 0.00e+00 fico_demean -0.00183 5.36e-05 -34.2 4.18e-256 Log(scale) -1.41070 2.65e-03 -532.9 0.00e+00 So given your transform the intercept term and log(scale) matches the a and b respectively - thanks a lot. The effect of fico_demean, however, still seems not close. I will try to find the KP book. Yes, the function which(rnos = bhaz * exp(dfico[i]*dficoeff))[1] is identical with min(which(rnos = bhaz * exp(dfico[i]*dficoeff))), because the vector of subscription returned by 'which' is always ascending. bhaz is not a constant but a vector of baseline hazard rate, so 'which' will do a element by element comparison. If bhaz is a constant, then endtime[i] will follow a geometric distribution. I appreciate your help. Thanks a lot. Jiakai Chen Terry Therneau wrote: The survreg function uses the location-scale parameterizations found in Kalbfleisch and Prentice's book The statistical analysis of failure time data. Looking at your code, you are using something different You KP 1/a lambda b gamma And from KP: lambda = exp(-alpha), gamma= 1/sigma, where alpha = linear predictor from the fit sigma = scale factor from the fit I would suggest checking out a copy of the book to verify the above. Second, your method of constructing a random time from the distribution is a mystery to me. I believe your code is equivalent to y - min(which(runif(n) constant)) for any given y (with changing values of the constant). This is a value from the geometic distribution. Terry Therneau __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- View this message in context: http://www.nabble.com/Survreg-function-for-loglogistic-hazard-estimation-tp23907598p23927718.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Survreg function for loglogistic hazard estimation
I am trying to use R to do loglogistic hazard estimation. My plan is to
generate a loglogistic hazard sample data and then use survreg to estimate
it. If everything is correct, survreg should return the parameters I have
used to generate the sample data.
I have written the following code to do a time invariant hazard estimation.
The output of summary(modloglog) shows the factor loading of dfico is -0.002
instead of 0.005. Also I can not find the survreg's output of alpha and
beta of loglogistic regression. Any comments? Thanks a lot,
Jiakai Chen
Code:
BEGIN==
# A time invariant loglogistic estimation
library(survival)
# Clear the workspace
rm(list = ls(all = TRUE))
# Totally 100K samples which may die during 100 periods
timeline = 100
samplesize = 10
dfico - rnorm(samplesize, mean = 0, sd = 25)
dficoeff - 0.005
# Baseline loglogistic hazard function stored in bhaz
a- 20
b - 4
time - 1:timeline
bhaz - ((b/a) * (time /a) ^ (b-1))/(1+(time/a)^b)
# Event time stored in endtime. Baseline hazard function is controlled by
# dfico value with factor loading dficoeff
endtime - numeric(samplesize)
for ( i in 1:samplesize) {
rnos - runif(timeline)
endtime[i] - which(rnos = bhaz * exp(dfico[i]*dficoeff))[1]
}
# Construct data frame
raw - data.frame(end = endtime, status = 1, fico_demean = dfico)
# Adding censorship
for( i in 1:samplesize) {
if(is.na(raw$end[i])) {raw$status[i] - 0}
}
for( i in 1:samplesize) {
if(is.na(raw$end[i])) {raw$end[i] - timeline }
}
# Output the factory
factory - factor(raw$end)
plot(factory)
# Use survreg to estimate the coefficents of loglogistic distribution
modloglog - survreg(Surv(end, status) ~ fico_demean, data = raw, model =
TRUE, dist = 'loglogistic')
summary(modloglog)
END==
--
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