Format bootstrap parameter estimate values and output selected columns to be shown in the bootstrap parameter table.
parameter estimates output from define_boot_table() with
modifications ready for formatting
logical (T/F). Defaults to TRUE, which selects the
following columns:
"abb", "desc", "boot_value", "boot_ci".
Set to FALSE to return all columns.
set significant digits for output (optional). Default is three digits
set maxex for computation (optional). Default is NULL
Deprecated. Please use .cleanup_cols instead. Columns
to select for output. To return all columns, specify "all".
model_dir <- system.file("model/nonmem", package = "pmparams")
paramKey <- file.path(model_dir, "pk-parameter-key-new.yaml")
# Using a file path:
boot_path <- file.path(model_dir, "boot/data/boot-106.csv")
boot_df <- define_boot_table(
.boot_estimates = boot_path,
.key = paramKey
)
format_boot_table(boot_df)
#> # A tibble: 15 × 4
#> abb desc boot_value boot_ci_95
#> <chr> <chr> <chr> <chr>
#> 1 KA (1/h) First order absorption rate constant 1.57 1.39, 1.78
#> 2 V2/F (L) Apparent central volume 61.5 58.3, 65.1
#> 3 CL/F (L/h) Apparent clearance 3.23 3.07, 3.42
#> 4 V3/F (L) Apparent peripheral volume 67.3 65.0, 69.8
#> 5 Q/F (L/h) Apparent intercompartmental clearance 3.61 3.37, 3.86
#> 6 CL/F ~ eGFR eGFR effect on CL/F 0.484 0.408, 0.558
#> 7 CL/F ~ Age Age effect on CL/F $-$0.0386 $-$0.167, 0.08…
#> 8 CL/F ~ ALB Serum albumin effect on CL/F 0.420 0.294, 0.587
#> 9 IIV-KA Variance of absorption 0.218 0.130, 0.331
#> 10 IIV-V2/F Variance of central volume 0.0821 0.0643, 0.101
#> 11 IIV-CL/F Variance of clearance 0.112 0.0896, 0.140
#> 12 V2/F-KA Covariance of V2/F - KA 0.0656 0.0328, 0.107
#> 13 CL/F-KA Covariance of CL/F - KA 0.121 0.0805, 0.173
#> 14 CL/F-V2/F Covariance of CL/F - V2/F 0.0696 0.0525, 0.0882
#> 15 Proportional Variance 0.0400 0.0376, 0.0424
# To include all columns:
format_boot_table(boot_df, .cleanup_cols = FALSE)
#> # A tibble: 15 × 25
#> parameter_names lower value upper ci_level name abb desc panel
#> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 THETA1 1.39 1.57 1.78 95 THETA1 KA (1/h) Firs… stru…
#> 2 THETA2 58.3 61.5 65.1 95 THETA2 V2/F (L) Appa… stru…
#> 3 THETA3 3.07 3.23 3.42 95 THETA3 CL/F (L… Appa… stru…
#> 4 THETA4 65.0 67.3 69.8 95 THETA4 V3/F (L) Appa… stru…
#> 5 THETA5 3.37 3.61 3.86 95 THETA5 Q/F (L/… Appa… stru…
#> 6 THETA6 0.408 0.484 0.558 95 THETA6 CL/F ~ … eGFR… cov
#> 7 THETA7 -0.167 -0.0386 0.0878 95 THETA7 CL/F ~ … Age … cov
#> 8 THETA8 0.294 0.420 0.587 95 THETA8 CL/F ~ … Seru… cov
#> 9 OMEGA(1,1) 0.130 0.218 0.331 95 OMEGA11 IIV-KA Vari… IIV
#> 10 OMEGA(2,2) 0.0643 0.0821 0.101 95 OMEGA22 IIV-V2/F Vari… IIV
#> 11 OMEGA(3,3) 0.0896 0.112 0.140 95 OMEGA33 IIV-CL/F Vari… IIV
#> 12 OMEGA(2,1) 0.0328 0.0656 0.107 95 OMEGA21 V2/F-KA Cova… IIV
#> 13 OMEGA(3,1) 0.0805 0.121 0.173 95 OMEGA31 CL/F-KA Cova… IIV
#> 14 OMEGA(3,2) 0.0525 0.0696 0.0882 95 OMEGA32 CL/F-V2… Cova… IIV
#> 15 SIGMA(1,1) 0.0376 0.0400 0.0424 95 SIGMA11 Proport… Vari… RV
#> # ℹ 16 more variables: trans <chr>, transTHETA <lgl>, THETAERR <lgl>, TH <lgl>,
#> # OM <lgl>, S <lgl>, LOG <lgl>, LOGIT <lgl>, lognormO <lgl>, Osd <lgl>,
#> # logitOsd <lgl>, propErr <lgl>, addErr <lgl>, addErrLogDV <lgl>,
#> # boot_value <chr>, boot_ci_95 <chr>
# Using a `bbr` bootstrap model object:
if (FALSE) { # \dontrun{
boot_run <- bbr::read_model(file.path(model_dir, "106-boot"))
boot_df <- define_boot_table(
.boot_estimates = bbr::bootstrap_estimates(boot_run),
.key = paramKey
) %>% format_boot_table()
} # }