Align data processing of predict() and modeling functions

[wlandau]

In this PR,pmrm uses all of pmrm_data() and rebuilds all ordered factors in predict(). Previously, predict() did only part of the processing from pmrm_data(). The following reprex now succeeds:

library(pmrm)
library(tidyverse)
set.seed(0L)
simulation <- pmrm_simulate_decline_proportional(
  visit_times = seq_len(5L) - 1
)
fit <- pmrm_model_decline_proportional(
  data = simulation,
  outcome = "y",
  time = "t",
  patient = "patient",
  visit = "visit",
  arm = "arm"
)
new_data <- tibble(
  patient = "pt_new_1",
  visit = factor(paste0("visit_", 1:5), ordered = T),
  t = 0:4,
  arm = "arm_1"
)
predict(fit, new_data)
#> # A tibble: 5 × 8
#>   patient  arm   visit    time  estimate standard_error  lower upper
#>   <fct>    <chr> <ord>   <int>     <dbl>          <dbl>  <dbl> <dbl>
#> 1 pt_new_1 arm_1 visit_1     0 -0.000613         0.0579 -0.114 0.113
#> 2 pt_new_1 arm_1 visit_2     1  0.702            0.0684  0.568 0.836
#> 3 pt_new_1 arm_1 visit_3     2  1.04             0.0732  0.895 1.18 
#> 4 pt_new_1 arm_1 visit_4     3  1.38             0.0770  1.23  1.53 
#> 5 pt_new_1 arm_1 visit_5     4  1.64             0.0834  1.48  1.81

^{Created on 2026-02-19 with reprex v2.1.1}

FYI @lbenz-lilly

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