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parameter-tables

parameter-tables.Rmd
library(hyperion)
#> 
#> 
#> ── pharos configuration ────────────────────────────────────────────────────────
#> ✔ pharos.toml found: /data/user-homes/tariq/projects/prism-pkgdocs-build/installed-pkgs/2026-03-02/hyperion.tables_0.3.0/vignettes/pharos.toml
#> ── hyperion options ────────────────────────────────────────────────────────────
#> ✔ hyperion.significant_number_display : 4
#> ── hyperion nonmem object options ──────────────────────────────────────────────
#> ✔ hyperion.nonmem_model.show_included_columns : FALSE
#> ✔ hyperion.nonmem_summary.rse_threshold : 50
#> ✔ hyperion.nonmem_summary.shrinkage_threshold : 30
library(hyperion.tables)

library(gt)
library(flextable)

model_dir <- system.file("extdata", "models", "onecmt", package = "hyperion.tables")
model_run <- "run003"
spec <- TableSpec() |>
  set_spec_transforms(omega = "cv") |>
  set_spec_sections(
    kind == "THETA" ~ "Structural model parameters",
    kind == "OMEGA" & diagonal ~ "Interindividual variance parameters",
    kind == "OMEGA" & !diagonal ~ "Interindividual covariance parameters",
    kind == "SIGMA" ~ "Residual error",
    TRUE ~ "Other"
  ) |>
  set_spec_parameter_names(source = "display") |>
  set_spec_title(paste(model_run, "Parameters"))

mod <- read_model(file.path(model_dir, paste0(model_run, ".mod")))

info <- get_model_parameter_info(
    mod,
  system.file("lookup.toml", package = "hyperion.tables")
)

info <- info |> 
  update_param_info("SIGMA(2,2)", parameterization = "AddErr")

mod_sum <- summary(mod)

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
run003 Parameters
Parameter Symbol Unit Estimate 95% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} L/hr 1.33 [1.11, 1.54] 8.41
Vc θ2\theta_{2} L 40.2 [34.6, 45.7] 7.07
KA θ3\theta_{3} 1/hr 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
PropErr Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
AddErr Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Changing display names with set_spec_parameter_names() 

spec <- spec |> set_spec_parameter_names(source = "display")

info <- info |>
    update_param_info("SIGMA(1,1)", display = "Proportional Error") |>
  update_param_info("SIGMA(2,2)", display = "Additive Error")

mod_sum <- summary(mod)

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
run003 Parameters
Parameter Symbol Unit Estimate 95% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} L/hr 1.33 [1.11, 1.54] 8.41
Vc θ2\theta_{2} L 40.2 [34.6, 45.7] 7.07
KA θ3\theta_{3} 1/hr 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
Proportional Error Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
Additive Error Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation 
spec <- spec |> set_spec_parameter_names(source = "nonmem")

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
run003 Parameters
Parameter Symbol Unit Estimate 95% CI RSE (%) Shrinkage (%)
Structural model parameters
THETA1 θ1\theta_{1} L/hr 1.33 [1.11, 1.54] 8.41
THETA2 θ2\theta_{2} L 40.2 [34.6, 45.7] 7.07
THETA3 θ3\theta_{3} 1/hr 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
OMEGA(1,1) THETA1 Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2 13.1
OMEGA(2,2) THETA2 Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7 4.63
OMEGA(3,3) THETA3 Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0 24.3
Interindividual covariance parameters
OMEGA(2,1) THETA1, THETA2 Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
SIGMA(1,1) Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
SIGMA(2,2) Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Adding descriptions with add_spec_columns() 

spec <- spec |>
  set_spec_parameter_names(source = "display") |>
  add_spec_columns("description")

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
run003 Parameters
Parameter Symbol Unit Estimate 95% CI RSE (%) Shrinkage (%)
Structural model parameters
CL Clearance θ1\theta_{1} L/hr 1.33 [1.11, 1.54] 8.41
Vc Central Volume θ2\theta_{2} L 40.2 [34.6, 45.7] 7.07
KA Absorption Rate Constant θ3\theta_{3} 1/hr 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
IIV-CL Interindividual variability on CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2 13.1
IIV-Vc Interindividual variability on Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7 4.63
IIV-KA Interindividual variability on KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Interindividual covariance for CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
Proportional Error Proportional Error Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
Additive Error Additive Error Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Removing columns with drop_spec_columns() 

## Start fresh to demonstrate drop_columns
spec <- TableSpec() |>
  set_spec_transforms(omega = "cv") |>
  set_spec_sections(
    kind == "THETA" ~ "Structural model parameters",
    kind == "OMEGA" & diagonal ~ "Interindividual variance parameters",
    kind == "OMEGA" & !diagonal ~ "Interindividual covariance parameters",
    kind == "SIGMA" ~ "Residual error",
    TRUE ~ "Other"
  ) |>
  set_spec_parameter_names(source = "display") |>
  drop_spec_columns("unit")

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Estimate 95% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} 1.33 [1.11, 1.54] 8.41
Vc θ2\theta_{2} 40.2 [34.6, 45.7] 7.07
KA θ3\theta_{3} 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
Proportional Error Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
Additive Error Σ(2,2)\Sigma_{(2,2)} 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation 
## Drop multiple columns
spec <- spec |> drop_spec_columns("shrinkage")

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Estimate 95% CI RSE (%)
Structural model parameters
CL θ1\theta_{1} 1.33 [1.11, 1.54] 8.41
Vc θ2\theta_{2} 40.2 [34.6, 45.7] 7.07
KA θ3\theta_{3} 1.21 [0.997, 1.43] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0236, 0.221] 41.2
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0519, 0.196] 29.7
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0121, 0.233] 46.0
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0131, 0.136] 42.0
Residual error
Proportional Error Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1
Additive Error Σ(2,2)\Sigma_{(2,2)} 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Structural parameters only 

sp_spec <- TableSpec() |>
  set_spec_sections(
    kind == "THETA" ~ "Structural model parameters",
    TRUE ~ "Other"
  ) |>
  set_spec_filter(kind == "THETA") |>
  drop_spec_columns("shrinkage")

get_parameters(mod) |>
  apply_table_spec(sp_spec, info) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Unit Estimate 95% CI RSE (%)
Structural model parameters
TVCL θ1\theta_{1} L/hr 1.33 [1.11, 1.54] 8.41
TVV θ2\theta_{2} L 40.2 [34.6, 45.7] 7.07
TVKA θ3\theta_{3} 1/hr 1.21 [0.997, 1.43] 9.06
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error

Random Effect Parameters only 

re_spec <- TableSpec() |>
  set_spec_sections(
    kind == "OMEGA" ~ "Random Effect Parameters",
    kind == "SIGMA" ~ "Residual Error",
    TRUE ~ "Other"
  ) |>
  set_spec_filter(kind != "THETA") |>
  drop_spec_columns("unit")

get_parameters(mod) |>
  apply_table_spec(re_spec, info) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Estimate 95% CI RSE (%) Shrinkage (%)
Random Effect Parameters
OM1 TVCL exp⁡(Ω(1,1))\exp(\Omega_{(1,1)}) 1.13 (CV = 36.1%) [1.02, 1.25] 41.2 13.1
OM1,2 TVCL, TVV exp⁡(Ω(2,1))\exp(\Omega_{(2,1)}) 1.08 (Corr = 0.606) [1.01, 1.15] 42.0
OM2 TVV exp⁡(Ω(2,2))\exp(\Omega_{(2,2)}) 1.13 (CV = 36.3%) [1.05, 1.22] 29.7 4.63
OM3 TVKA exp⁡(Ω(3,3))\exp(\Omega_{(3,3)}) 1.13 (CV = 36.1%) [1.01, 1.26] 46.0 24.3
Residual Error
SIG1 Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0257, 0.0494] 16.1 14.4
SIG2 Σ(2,2)\Sigma_{(2,2)} 0.00527 (SD = 0.0726) [-0.0128, 0.0233] 175 14.4
95% CI: Estimate±z0.025⋅SE\mathrm{Estimate} \pm z_{0.025} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Confidence Interval level 

spec <- TableSpec() |>
  set_spec_transforms(omega = "cv") |>
  set_spec_sections(
    kind == "THETA" ~ "Structural model parameters",
    kind == "OMEGA" & diagonal ~ "Interindividual variance parameters",
    kind == "OMEGA" & !diagonal ~ "Interindividual covariance parameters",
    kind == "SIGMA" ~ "Residual variance",
    TRUE ~ "Other"
  ) |>
  set_spec_ci(level = 0.7) |>
  set_spec_sigfig(3)

mod_sum <- summary(mod)
info <- get_model_parameter_info(mod)

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Unit Estimate 70% CI RSE (%) Shrinkage (%)
Structural model parameters
TVCL θ1\theta_{1} L/hr 1.33 [1.21, 1.44] 8.41
TVV θ2\theta_{2} L 40.2 [37.2, 43.1] 7.07
TVKA θ3\theta_{3} 1/hr 1.21 [1.10, 1.33] 9.06
Interindividual variance parameters
OM1 TVCL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0702, 0.175] 41.2 13.1
OM2 TVV Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0858, 0.162] 29.7 4.63
OM3 TVKA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0641, 0.181] 46.0 24.3
Interindividual covariance parameters
OM1,2 TVCL, TVV Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0421, 0.107] 42.0
Residual variance
SIG1 Σ(1,1)\Sigma_{(1,1)} 0.0375 (SD = 0.194) [0.0313, 0.0438] 16.1 14.4
SIG2 Σ(2,2)\Sigma_{(2,2)} 0.00527 (SD = 0.0726) [-0.00427, 0.0148] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826 | Condition Number: 6.17
70% CI: Estimate±z0.15⋅SE\mathrm{Estimate} \pm z_{0.15} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Changing summary info shown 

spec <- TableSpec() |>
  set_spec_transforms(omega = "cv") |>
  set_spec_sections(
    kind == "THETA" ~ "Structural model parameters",
    kind == "OMEGA" & diagonal ~ "Interindividual variance parameters",
    kind == "OMEGA" & !diagonal ~ "Interindividual covariance parameters",
    kind == "SIGMA" ~ "Residual variance",
    TRUE ~ "Other"
  ) |>
  set_spec_ci(level = 0.7) |>
  set_spec_sigfig(3) |>
  set_spec_parameter_names(source = "display")

mod_sum <- summary(mod)
info <- get_model_parameter_info(mod, lookup_path = normalizePath("../inst/lookup.toml"))

get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum, show_cond_num = FALSE) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Unit Estimate 70% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} L/hr 1.33 [1.21, 1.44] 8.41
Vc θ2\theta_{2} L 40.2 [37.2, 43.1] 7.07
KA θ3\theta_{3} 1/hr 1.21 [1.10, 1.33] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0702, 0.175] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0858, 0.162] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0641, 0.181] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0421, 0.107] 42.0
Residual variance
PropErr Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0313, 0.0438] 16.1 14.4
AddErr Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.00427, 0.0148] 175 14.4
First Order Conditional Estimation with Interaction | Objective function value: -109.826
70% CI: Estimate±z0.15⋅SE\mathrm{Estimate} \pm z_{0.15} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation 
get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum, show_cond_num = FALSE, show_ofv = FALSE) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Unit Estimate 70% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} L/hr 1.33 [1.21, 1.44] 8.41
Vc θ2\theta_{2} L 40.2 [37.2, 43.1] 7.07
KA θ3\theta_{3} 1/hr 1.21 [1.10, 1.33] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0702, 0.175] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0858, 0.162] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0641, 0.181] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0421, 0.107] 42.0
Residual variance
PropErr Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0313, 0.0438] 16.1 14.4
AddErr Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.00427, 0.0148] 175 14.4
First Order Conditional Estimation with Interaction
70% CI: Estimate±z0.15⋅SE\mathrm{Estimate} \pm z_{0.15} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation 
get_parameters(mod) |>
  apply_table_spec(spec, info) |>
  add_summary_info(mod_sum, show_method = FALSE) |>
  make_parameter_table()
Model Parameters
Parameter Symbol Unit Estimate 70% CI RSE (%) Shrinkage (%)
Structural model parameters
CL θ1\theta_{1} L/hr 1.33 [1.21, 1.44] 8.41
Vc θ2\theta_{2} L 40.2 [37.2, 43.1] 7.07
KA θ3\theta_{3} 1/hr 1.21 [1.10, 1.33] 9.06
Interindividual variance parameters
IIV-CL Ω(1,1)\Omega_{(1,1)} 0.122 (CV = 36.1%) [0.0702, 0.175] 41.2 13.1
IIV-Vc Ω(2,2)\Omega_{(2,2)} 0.124 (CV = 36.3%) [0.0858, 0.162] 29.7 4.63
IIV-KA Ω(3,3)\Omega_{(3,3)} 0.122 (CV = 36.1%) [0.0641, 0.181] 46.0 24.3
Interindividual covariance parameters
IIV-CL-Vc Ω(2,1)\Omega_{(2,1)} 0.0745 (Corr = 0.606) [0.0421, 0.107] 42.0
Residual variance
PropErr Σ(1,1)\Sigma_{(1,1)} 0.0375 (CV = 19.4%) [0.0313, 0.0438] 16.1 14.4
AddErr Σ(2,2)\Sigma_{(2,2)} ng/mL 0.00527 (SD = 0.0726) [-0.00427, 0.0148] 175 14.4
Objective function value: -109.826 | Condition Number: 6.17
70% CI: Estimate±z0.15⋅SE\mathrm{Estimate} \pm z_{0.15} \cdot \mathrm{SE}
CV% for log-normal Ω\Omega: exp⁡(Estimate)−1×100\sqrt{\exp(\mathrm{Estimate}) - 1} \times 100
CV% for proportional Σ\Sigma: Estimate×100\sqrt{\mathrm{Estimate}} \times 100
Abbreviations:
CI = confidence intervals; RSE = relative standard error; SE = standard error;
CV = coefficient of variation; SD = standard deviation; Corr = correlation

Transformation Reference

The following table shows how CV, RSE, and CI are computed for each transform and parameter type combination.

Transformation Formulas
Parameter CV RSE1 CI2
Identity Theta N/A
Omega N/A
Sigma N/A
LogNormal Theta N/A exp⁡(SE2)−1\sqrt{\exp(\text{SE}^2) - 1} exp⁡(Est±z⋅SE)\exp(\text{Est} \pm z \cdot \text{SE})
Omega exp⁡(Est)−1\sqrt{\exp(\text{Est}) - 1} exp⁡(Est±z⋅SE)\exp(\text{Est} \pm z \cdot \text{SE})
Sigma exp⁡(Est)−1\sqrt{\exp(\text{Est}) - 1} exp⁡(Est±z⋅SE)\exp(\text{Est} \pm z \cdot \text{SE})
Logit Theta N/A (1−BT)⋅SE(1 - \text{BT}) \cdot \text{SE} 11+exp⁡(−(Est±z⋅SE))\frac{1}{1 + \exp(-(\text{Est} \pm z \cdot \text{SE}))}
Omega N/A 11+exp⁡(−(Est±z⋅SE))\frac{1}{1 + \exp(-(\text{Est} \pm z \cdot \text{SE}))}
Sigma N/A 11+exp⁡(−(Est±z⋅SE))\frac{1}{1 + \exp(-(\text{Est} \pm z \cdot \text{SE}))}
Proportional Theta N/A
Omega Est\sqrt{\text{Est}}
Sigma Est\sqrt{\text{Est}}
AddErr Theta N/A
Omega N/A
Sigma N/A
LogAddErr Theta exp⁡(Est2)−1\sqrt{\exp(\text{Est}^2) - 1}
Omega N/A
Sigma exp⁡(Est)−1\sqrt{\exp(\text{Est}) - 1}
Est = THETA(x)/OMEGA(i,j)/SIGMA(i,j) reported in the .ext file
BT = back-transformed estimate = 1/(1 + exp(-Est))
SE = Standard Error, z = z-score for CI level
CV and RSE formulas are multiplied by 100 to express as percentages
1 SE/|Est| unless otherwise noted
2 Est ± z·SE unless otherwise noted

Model Lineage 

example_tree <- get_model_lineage(model_dir)

example_tree

Hyperion Model Tree

ℹ️ Models: 8

  • run001 - Base model
    • run004 - Updating run001 to run004 with jittered params …
    • run002 - Adding COV step, unfixing eps(2)
      • run002a - Some description about what makes run002a diffe…
      • run002b001 - Jittering initial sigma estimates, using theta/…
      • run003 - Jittering initial estimates
        • run003b2 - Updating run003 with mod object
        • run003b1 - Updating run003 to 003b1 with jittered params. … 
spec <- SummarySpec() |>
  set_spec_pvalue(scientific = FALSE)

example_tree |>
  apply_summary_spec(spec) |>
  make_summary_table()
Run Summary
Model Reference Description No. Params Cond. No. OFV Δ\DeltaOFV p-value
run001 Base model 6 1.98 -103.299
run002 run001 Adding COV step, unfixing eps(2) 8 29.6 -103.468 -0.169 0.919 (df = 2)
run003 run002 Jittering initial estimates 9 6.17 -109.826 -6.358 0.0117 (df = 1)
run003b1 run003 Updating run003 to 003b1 with jittered params. Adding WT on V 10 -108.889 0.937 1 (df = 1)
Abbreviations:
OFV = Objective Function Value; ΔOFV = change in OFV from reference model;
Cond. No. = Condition Number; p-value from LRT (Likelihood Ratio Test); df =
degrees of freedom