Format bootstrap parameter estimate values and output selected columns to be shown in the bootstrap parameter table.

format_boot_table(
  .boot_df,
  .cleanup_cols = TRUE,
  .digit = getOption("pmparams.dig"),
  .maxex = getOption("pmparams.maxex"),
  .select_cols = NULL
)

Arguments

.boot_df

parameter estimates output from define_boot_table() with modifications ready for formatting

.cleanup_cols

logical (T/F). Defaults to TRUE, which selects the following columns:

  • "abb", "desc", "boot_value", "boot_ci".

  • Set to FALSE to return all columns.

.digit

set significant digits for output (optional). Default is three digits

.maxex

set maxex for computation (optional). Default is NULL

.select_cols

Deprecated. Please use .cleanup_cols instead. Columns to select for output. To return all columns, specify "all".

Examples


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()
} # }