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Read NONMEM 7.2+ output into an R object.

Source: R/rnm.R
rnm.Rd

Read NONMEM 7.2+ output into an R object.

Usage

rnm(
  index,
  prefix = "run",
  pathNM,
  ndig = 3,
  ndigB = 3,
  ndigP = 1,
  Pci = 95,
  ext = ".lst",
  extmod = ".mod",
  Pvalues = TRUE,
  RawCI = FALSE,
  ...
)

Arguments

index

The NONMEM model index, i.e. the numeric part of the filename assuming it follows the convention 'run123.mod'.

prefix

The NONMEM model prefix, assuming it follows the convention 'run123.mod'. The default is "run".

pathNM

The path to the NONMEM output. This should not contain a trailing slash.

ndig

Number of significant digits to use. The default is 3.

ndigB

Number of significant digits to use. The default is 3.

ndigP

Number of digits after the decimal point to use for percentages. The default is 1.

Pci

Asymptotic confidence interval to apply when reporting parameter uncertainty. The default is 95.

ext

NONMEM output file extension. The default is ".lst".

extmod

NONMEM control stream file extension. The default is "mod".

Pvalues

Report P-values for parameters? The default is TRUE.

RawCI

Report confidence intervals without estimate? The default is FALSE.

...

Additional arguments.

Value

A list containing information extracted from the NONMEM output.

Details

The output list is composed of the following objects:

  • Theta: A data frame describing the structural (fixed-effect) parameters, containing parameter name, estimated value, standard error (SE), coefficient of variation (CV), lower and upper confidence limits (CIL and CIU, based on Pci), and P-value, calculated as 2\*(1-pnorm(abs(theta/theta.se))).

  • Eta: A data frame describing the interindividual random-effects parameters, containing estimated value, standard error (SE), coefficient of variation (CV, calculated as abs(100*(SE/OMEGA))), coefficient of variation (EtaCV, calculated as 100*sqrt(OMEGA)), and shrinkage.

  • Epsilon: A data frame describing the residual random-effects parameters, containing estimated value, standard error (SE), coefficient of variation (CV, calculated as abs(100*(SE/OMEGA))), coefficient of variation (EtaCV, calculated as 100*sqrt(SIGMA)), and shrinkage.

  • CorTheta: A data frame containing the correlation matrix for fixed effects (THETA).

  • CorOmega: A data frame containing the correlation matrix for interindividual random effects (OMEGA).

  • CorSigma: A data frame containing the correlation matrix for residual random effects (SIGMA).

  • OmegaMatrix: A data frame containing the OMEGA matrix.

  • SigmaMatrix: A data frame containing the SIGMA matrix.

  • CovMatrixTheta: A data frame containing the variance-covariance matrix for structural parameters (THETA).

  • CovMatrix: A data frame containing the complete variance-covariance matrix.

  • OFV: The objective function value.

  • ThetaString: A data frame containing all relevant fixed-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate, standard error, coefficient of variation, combined estimate and asymptotic confidence interval, and P-value.

  • EtaString: A data frame containing all relevant interindivudal random-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate (variance), standard error, coefficient of variation, percentage value (calculated as 100*sqrt(OMEGA)), and shrinkage.

  • EpsString: A data frame containing all relevant residual random-effects parameter information, suitable for use in a table of parameter estimates. Contains parameter name, estimate (variance), standard error, coefficient of variation, percentage value (calculated as 100*sqrt(SIGMA)), and shrinkage.

  • RunTime: Run time.

  • ConditionN: Condition number.

See also

NONMEM (https://www.iconplc.com/solutions/technologies/nonmem)

Author

Rik Schoemaker, rik.schoemaker@occams.com

Justin Wilkins, justin.wilkins@occams.com

Examples

if (FALSE) { # \dontrun{
nmOutput <- rnm("run315.lst")
} # }