Try deal with the xlevs stuff

Author: sambrilleman

R/pp_data.R

@@ -355,7 +355,7 @@ pp_data <-
     mf[, colnames(mf_s)] <- mf_s
 
     # construct time-varying predictor matrix
-    s <- make_s(formula, mf, xlevs = object$xlevs) 
+    s <- make_s(formula, mf)
 
     if (all(is.na(pts))) {
       # if pts were all NA then replace the time-varying predictor

R/stan_surv.R

@@ -748,7 +748,7 @@ stan_surv <- function(formula,
   if (has_tve) {
 
     # time-varying predictor matrix
-    s_cpts          <- make_s(formula, mf_cpts, xlevs = xlevs)
+    s_cpts          <- make_s(formula, mf_cpts)
     smooth_map      <- get_smooth_name(s_cpts, type = "smooth_map")
     smooth_idx      <- get_idx_array(table(smooth_map))
     S <- ncol(s_cpts) # number of tve coefficients