I am building known fate survival models based on numerous covariates including study site. At some sites, all individuals survived for the entire study period, making the site's S = 1.000 in the models. While this result is accurate, it is causing the standard error for that site to become 0 or a very large value. In one of my competing models (which includes site as a covariate), all standard error values are 0, including sites that had mortality and therefore should have an estimable value for standard error. Models that do not contain site as a covariate seem completely fine.
This is what my code looks like for processing data, creating design data, creating a function for running competing models (I shortened the list of models for this example- the function actually contains ~40 total models), and examining real parameters from the top model:
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#Process Data and designate groups
Surv <- process.data(data, model = "Known", groups = c("Sex", "Site"))
#Create Design Data
Surv.ddl <- make.design.data(Surv)
#Create function to run models specified within function
run.surv <- function() {
S.Sex <- list(formula= ~Sex)
S.Site <- list(formula= ~Site)
# Create model list
model.list = create.model.list("Known")
Surv.results = mark.wrapper(model.list, data = Surv,
ddl = Surv.ddl, output = FALSE, silent = TRUE)
# Return model table and list of models
return(Surv.results)
}
#View results
Surv.results = run.surv()
Surv.results
#top model= site
summary(Surv.results$S.Site)
Here, also, is the output of that summary function where you can see the standard error values and confidence intervals that are odd for sites that have S=1.000 (Sites D and E, not the intercept site).
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Beta
estimate se lcl ucl
S:(Intercept) 3.3063687 0.000000 3.3063687 3.306369
S:SiteB 0.6056572 1.009952 -1.3738480 2.585162
S:SiteC 1.8294433 1.002944 -0.1363261 3.795213
S:SiteD 24.3810510 0.000000 24.3810510 24.381051
S:SiteE 18.7342030 3913.228200 -7651.1933000 7688.661700
Since I am getting such odd values for standard error, I want to ensure that my other parameter estimates are accurate before moving on with manuscript preparation. Is there an alternative way to get a standard error or confidence interval for these models that have S=1.000 for some sites?
I apologize if previous answers have provided insight on this topic- this is my first survival analysis so I tried my best to read other answers but tend to get lost in the weeds. Thank you so much in advance for any insight you can provide!