These functions modify the simulated data in an mrgsims object and return the modified object. Contrast with the functions in mrgsims_dplyr.
Examples
out <- mrgsim(house(), events = ev(amt = 100))
filter_sims(out, time > 2)
#> Model: housemodel
#> Dim: 472 x 7
#> Time: 2.25 to 120
#> ID: 1
#> ID time GUT CENT RESP DV CP
#> 1: 1 2.25 6.721 86.23 35.84 4.312 4.312
#> 2: 1 2.50 4.979 86.89 35.46 4.345 4.345
#> 3: 1 2.75 3.688 87.09 35.22 4.355 4.355
#> 4: 1 3.00 2.732 86.96 35.07 4.348 4.348
#> 5: 1 3.25 2.024 86.59 34.99 4.329 4.329
#> 6: 1 3.50 1.500 86.03 34.97 4.302 4.302
#> 7: 1 3.75 1.111 85.35 34.98 4.267 4.267
#> 8: 1 4.00 0.823 84.57 35.03 4.229 4.229
mutate_sims(out, label = "abc")
#> Model: housemodel
#> Dim: 482 x 8
#> Time: 0 to 120
#> ID: 1
#> ID time GUT CENT RESP DV CP label
#> 1: 1 0.00 0.00 0.00 50.00 0.000 0.000 abc
#> 2: 1 0.00 100.00 0.00 50.00 0.000 0.000 abc
#> 3: 1 0.25 74.08 25.75 48.68 1.287 1.287 abc
#> 4: 1 0.50 54.88 44.50 46.18 2.225 2.225 abc
#> 5: 1 0.75 40.66 58.08 43.61 2.904 2.904 abc
#> 6: 1 1.00 30.12 67.83 41.38 3.391 3.391 abc
#> 7: 1 1.25 22.31 74.74 39.58 3.737 3.737 abc
#> 8: 1 1.50 16.53 79.56 38.18 3.978 3.978 abc
select_sims(out, RESP, CP)
#> Model: housemodel
#> Dim: 482 x 4
#> Time: 0 to 120
#> ID: 1
#> ID time RESP CP
#> 1: 1 0.00 50.00 0.000
#> 2: 1 0.00 50.00 0.000
#> 3: 1 0.25 48.68 1.287
#> 4: 1 0.50 46.18 2.225
#> 5: 1 0.75 43.61 2.904
#> 6: 1 1.00 41.38 3.391
#> 7: 1 1.25 39.58 3.737
#> 8: 1 1.50 38.18 3.978