Summarize parameter estimates and run information from an nlmixr2 fit

Extracts fixed effects, between-subject variability, residual variability, estimation precision, confidence intervals, covariance structure, shrinkage, and key runtime metrics from a fitted model produced by nlmixr2.

Usage

get.mod.lst(fit.s, modi)

Arguments

fit.s

A model object generated using nlmixr2.

modi

A numeric identifier used to label the model results, for example when multiple models are evaluated in sequence.

Value

A data.frame with parameter summaries, model fit criteria (AIC, BIC, objective function value, log-likelihood, number of estimated parameters) and computation timings extracted from the fitted object.

Details

The function checks for the presence of each element before extraction to ensure robust handling of incomplete estimation or missing covariance results.

Author

Zhonghui Huang

Examples

# \donttest{
pheno <- function() {
  ini({
    tcl <- log(0.008) # typical value of clearance
    tv <-  log(0.6)   # typical value of volume
    eta.cl + eta.v ~ c(1,
                       0.01, 1) ## cov(eta.cl, eta.v), var(eta.v)
    add.err <- 0.1    # residual variability
  })
  model({
    cl <- exp(tcl + eta.cl) # individual value of clearance
    v <- exp(tv + eta.v)    # individual value of volume
    ke <- cl / v            # elimination rate constant
    d/dt(A1) = - ke * A1    # model differential equation
    cp = A1 / v             # concentration in plasma
    cp ~ add(add.err)       # define error model
  })
}

# Fit the model using nlmixr2
fit <- nlmixr2est::nlmixr2(pheno, pheno_sd, est="saem", nlmixr2est::saemControl(print=0))
#>  
#>  
#>  
#>  
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#>  
#> → loading into symengine environment...
#> → pruning branches (`if`/`else`) of saem model...
#> ✔ done
#> → finding duplicate expressions in saem model...
#> ✔ done
#> ℹ calculate uninformed etas
#> ℹ done
#> Calculating covariance matrix
#> → loading into symengine environment...
#> → pruning branches (`if`/`else`) of saem model...
#> ✔ done
#> → finding duplicate expressions in saem predOnly model 0...
#> → finding duplicate expressions in saem predOnly model 1...
#> → finding duplicate expressions in saem predOnly model 2...
#> ✔ done
#>  
#>  
#> → Calculating residuals/tables
#> ✔ done
#> → compress origData in nlmixr2 object, save 34224
#> → compress parHistData in nlmixr2 object, save 7200
#> → compress phiM in nlmixr2 object, save 1021696

# Extract model results
model_results <- get.mod.lst(fit,1)
print(model_results)
#>   model.num        current.time AIC BIC OBJFV ll npar model.covMethod
#> 1         1 2026-07-23 00:01:01  NA  NA    NA NA   NA          linFim
#>   model.message model.time.setup model.time.covariance model.time.algorithm
#> 1                      0.0288852             0.0140033                9.879
#>   model.time.optimize model.time.table model.time.compress model.time.other
#> 1                  NA            0.087               0.114        0.7891115
#>   thetaka thetacl thetavc thetavp thetavp2 thetaq thetaq2 thetavmax thetakm
#> 1      NA      NA      NA      NA       NA     NA      NA        NA      NA
#>   thetaD2 thetaF1 thetaF2 thetatlag thetamtt thetan thetabio rseka rsecl rsevc
#> 1      NA      NA      NA        NA       NA     NA       NA    NA    NA    NA
#>   rsevp rsevp2 rseq rseq2 rsevmax rsekm rseD2 rseF1 rseF2 rsetlag rsemtt rsen
#> 1    NA     NA   NA    NA      NA    NA    NA    NA    NA      NA     NA   NA
#>   rsebio bsvka bsvcl bsvvc bsvvp bsvvp2 bsvq bsvq2 bsvvmax bsvkm bsvD2 bsvF1
#> 1     NA    NA    NA    NA    NA     NA   NA    NA      NA    NA    NA    NA
#>   bsvF2 bsvtlag bsvmtt bsvn bsvbio shrinkka shrinkcl shrinkvc shrinkvp
#> 1    NA      NA     NA   NA     NA       NA       NA       NA       NA
#>   shrinkvp2 shrinkq shrinkq2 shrinkvmax shrinkkm shrinkD2 shrinkF1 shrinkF2
#> 1        NA      NA       NA         NA       NA       NA       NA       NA
#>   shrinktlag shrinkmtt shrinkn shrinkbio CIlowerka CIlowercl CIlowervc
#> 1         NA        NA      NA        NA        NA        NA        NA
#>   CIlowervp CIlowervp2 CIlowerq CIlowerq2 CIlowervmax CIlowerkm CIlowerD2
#> 1        NA         NA       NA        NA          NA        NA        NA
#>   CIlowerF1 CIlowerF2 CIlowertlag CIlowermtt CIlowern CIlowerbio CIupperka
#> 1        NA        NA          NA         NA       NA         NA        NA
#>   CIuppercl CIuppervc CIuppervp CIuppervp2 CIupperq CIupperq2 CIuppervmax
#> 1        NA        NA        NA         NA       NA        NA          NA
#>   CIupperkm CIupperD2 CIupperF1 CIupperF2 CIuppertlag CIuppermtt CIuppern
#> 1        NA        NA        NA        NA          NA         NA       NA
#>   CIupperbio omegaka   omegacl omegavc omegavp omegavp2 omegaq omegaq2
#> 1         NA      NA 0.2376906      NA      NA       NA     NA      NA
#>   omegavmax omegakm omegaD2 omegaF1 omegaF2 omegatlag omegamtt omegan omegabio
#> 1        NA      NA      NA      NA      NA        NA       NA     NA       NA
#>   omega.vc.cl omega.vp.cl omega.q.cl omega.vp2.cl omega.q2.cl omega.vp.vc
#> 1          NA          NA         NA           NA          NA          NA
#>   omega.q.vc omega.vp2.vc omega.q2.vc omega.q.vp omega.vp2.vp omega.q2.vp
#> 1         NA           NA          NA         NA           NA          NA
#>   omega.vp2.q omega.q2.q omega.q2.vp2 omega.vmax.km cor.eta.vc.cl cor.eta.vp.cl
#> 1          NA         NA           NA            NA            NA            NA
#>   cor.eta.q.cl cor.eta.vp2.cl cor.eta.q2.cl cor.eta.vp.vc cor.eta.q.vc
#> 1           NA             NA            NA            NA           NA
#>   cor.eta.vp2.vc cor.eta.q2.vc cor.eta.q.vp cor.eta.vp2.vp cor.eta.q2.vp
#> 1             NA            NA           NA             NA            NA
#>   cor.eta.vp2.q cor.eta.q2.q cor.eta.q2.vp2 cor.eta.vmax.km add prop
#> 1            NA           NA             NA              NA  NA   NA
# }