now we have it ....

models/msm_age/fit.R

@@ -21,7 +21,8 @@ df_gose <- readRDS(inputfile) %>%
   ) %>% select(
     gupi,
     Outcomes.DerivedCompositeGOSE,
-    Outcomes.DerivedCompositeGOSEDaysPostInjury
+    Outcomes.DerivedCompositeGOSEDaysPostInjury,
+    Subject.Age
   ) %>%
   arrange(
     gupi,
@@ -30,11 +31,12 @@ df_gose <- readRDS(inputfile) %>%
 
 # translate to msm formatting
 tmp <- df_gose %>%
-  rbind(tibble( # only predict GOSE at 180 days - takes too long otherwise
-    gupi   = df_gose$gupi %>% unique,
+  group_by(gupi) %>%
+  summarize_all(first) %>%
+  mutate(
     Outcomes.DerivedCompositeGOSEDaysPostInjury = config$t_out_msm + .5, # needed to offset
     Outcomes.DerivedCompositeGOSE = 99
-  )) %>%
+  ) %>%
   arrange(gupi, Outcomes.DerivedCompositeGOSEDaysPostInjury) %>%
   mutate(
     obstype = ifelse(Outcomes.DerivedCompositeGOSE == 1, 3, 1), # make death exactly observed transition
@@ -69,11 +71,11 @@ fit <- msm(
   subject   = tmp$gupi,
   data      = tmp,
   obstype   = tmp$obstype,
+  covariates = ~ age,
   gen.inits = TRUE,
   qmatrix   = Q,
   censor    = 99,
   pci       = c(90, 270),
-  covariates = ~ Subject.Age,
   censor.states = 1:7,
   control   = list(
     fnscale = config$fnscale_msm,