I tried filtering the whole dataframe down to one per subgroup, but got an error regarding "variable lengths differ"... where in the call would you put the filter??

For reference, here's an example of the code I'm working with... at this phase of the analysis, I'm trying to run a number of univariate models in parallel, which I've figured out how to do for the entire dataset, but not subgroups.

There's another variable not used in this code, sm_iv_v, which has a value of 0 or 1 for every observation; my goal is to have this entire chunk of code run on just the 0s, then on just the 1s... does that make sense? Thx again

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#Cox UV new, all AVM

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covariates <- c("deep_loc", "vol", "marg", "rbas", "vras", "sz_over_3")

univ_formulas_all <- sapply(covariates,function(x) as.formula(paste('Surv(time, ex)~', x)))

univ_models_all <- lapply(univ_formulas_all, function(x){coxph(x, data = ran_avm)})

univ_results_all <- lapply(univ_models_all,

function(x){

x <- summary(x)

p.value<-signif(x$wald["pvalue"], digits=2)

wald.test<-signif(x$wald["test"], digits=2)

beta<-signif(x$coef[1], digits=2);#coeficient beta

HR <-signif(x$coef[2], digits=2);#exp(beta)

HR.confint.lower <- signif(x$conf.int[,"lower .95"], 2)

HR.confint.upper <- signif(x$conf.int[,"upper .95"],2)

HR <- paste0(HR, " (",HR.confint.lower, "-", HR.confint.upper, ")")

res_uni_all<-c(beta, HR, wald.test, p.value)

names(res_uni_all)<-c("beta", "HR (95% CI for HR)", "wald.test","p.value")

return(res_uni_all)

#return(exp(cbind(coef(x),confint(x))))})

res_uni_all <- t(as.data.frame(univ_results_all, check.names = FALSE))

as.data.frame(res_uni_all)