add_cif assumes causes with numeric labels?

[fabian-s]

In the reprex below, everything works fine for cause= 1/2; but not cause= Death/Discharge:

library(pammtools)
#> 
#> Attaching package: 'pammtools'
#> The following object is masked from 'package:stats':
#> 
#>     filter
data(sir.adm, package = "mvna")
ped <- as_ped(sir.adm, Surv(time, status)~ pneu, combine = TRUE) |>
  mutate(cause = factor(cause, labels = c("Death", "Discharge"))) #!!
pam <- pamm(ped_status ~ s(tend, by = cause) + cause*pneu, data = ped)
summary(pam)
#> 
#> Family: poisson 
#> Link function: log 
#> 
#> Formula:
#> ped_status ~ s(tend, by = cause) + cause * pneu
#> 
#> Parametric coefficients:
#>                     Estimate Std. Error z value Pr(>|z|)    
#> (Intercept)         -2.60477    0.04316 -60.358  < 2e-16 ***
#> causeDischarge      -2.35417    0.14266 -16.502  < 2e-16 ***
#> pneu                -1.07039    0.13009  -8.228  < 2e-16 ***
#> causeDischarge:pneu  0.93058    0.29722   3.131  0.00174 ** 
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Approximate significance of smooth terms:
#>                         edf Ref.df Chi.sq  p-value    
#> s(tend):causeDeath     8.52  8.906 31.101 0.000671 ***
#> s(tend):causeDischarge 4.08  4.990  9.453 0.095237 .  
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> R-sq.(adj) =  0.0329   Deviance explained = 14.3%
#> UBRE = -0.78348  Scale est. = 1         n = 19338

ndf <- ped |> make_newdata(tend  = unique(tend), pneu  = unique(pneu), cause = unique(cause))
ndf <- ndf |>
  group_by(cause, pneu) |> # important!
  add_cif(pam)
#> Warning in predict.gam(object, .df, type = "lpmatrix"): factor levels 1 not in
#> original fit
#> Error in `map()`:
#> ℹ In index: 1.
#> ℹ With name: 1.
#> Caused by error in `map()`:
#> ℹ In index: 1.
#> Caused by error in `X[, pstart[i] - 1 + 1:object$nsdf[i]] <- Xp`:
#> ! replacement has length zero
#> Backtrace:
#>      ▆
#>   1. ├─pammtools::add_cif(group_by(ndf, cause, pneu), pam)
#>   2. ├─pammtools:::add_cif.default(group_by(ndf, cause, pneu), pam)
#>   3. │ └─purrr::map_dfr(...)
#>   4. │   └─purrr::map(.x, .f, ...)
#>   5. │     └─purrr:::map_("list", .x, .f, ..., .progress = .progress)
#>   6. │       ├─purrr:::with_indexed_errors(...)
#>   7. │       │ └─base::withCallingHandlers(...)
#>   8. │       ├─purrr:::call_with_cleanup(...)
#>   9. │       └─pammtools (local) .f(.x[[i]], ...)
#>  10. │         ├─pammtools:::get_cif(...)
#>  11. │         └─pammtools:::get_cif.default(...)
#>  12. │           └─purrr::map(...)
#>  13. │             └─purrr:::map_("list", .x, .f, ..., .progress = .progress)
#>  14. │               ├─purrr:::with_indexed_errors(...)
#>  15. │               │ └─base::withCallingHandlers(...)
#>  16. │               ├─purrr:::call_with_cleanup(...)
#>  17. │               └─pammtools (local) .f(.x[[i]], ...)
#>  18. │                 ├─stats::predict(object, .df, type = "lpmatrix")
#>  19. │                 └─mgcv::predict.gam(object, .df, type = "lpmatrix")
#>  20. └─base::.handleSimpleError(...)
#>  21.   └─purrr (local) h(simpleError(msg, call))
#>  22.     └─cli::cli_abort(...)
#>  23.       └─rlang::abort(...)

^{Created on 2023-07-12 with reprex v2.0.2}

Session info

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#> ──────────────────────────────────────────────────────────────────────────────

Digging deeper, the error is in get_cif:

pammtools/R/add-functions.R

Lines 724 to 730 in 94e7ea1

	hazards <- map(
	causes_model,
	~ {
	.df <- mutate(newdata, cause = .x) %>%
	arrange(.data[[time_var]], .by_group = TRUE)
	X <- predict(object, .df, type = "lpmatrix")
	apply(sim_coef_mat, 1, function(z) exp(X %*% z))

where causes_model from the attr_ped$risks-slot of the fitted PAMM used for map is a factor with levels 1, 2 but causein newdata has the text labels