release_notes.RmdPRED is now output as a separate column in the file
output of vpcmodel(). Previously, PRED was
output in the DV column with
REPLICATE =-1.
LLOQ value is now outputted to predcheck0 (Observations data
frame) for vpcmodel() function.
For each observed variable per each replicate, predout (PredCheckAll worksheet) now lists simulated values, population predictions if either OutputPRED is requested or prediction correction is enabled, correction factor and corrected simulated value if predication correction is enabled.
RsNLME print() model generic displays the values of
modelName and workingDir slots.
A new wrapper function called hostParams() allows
setup of host objects without using the NlmeParallelHost class
initializer.
A new wrapper function called tableParams() allows
defining table output instead of using
NlmeTableDef-class/NlmeSimTableDef-class
initializers.
The syntax for the colMapping() function now allows
for unquoted key-value pairs that may be specified via the ellipses
argument.
A new filesToReturn argument is available for the fitmodel() and sortfit() functions, which allows specification of data tables to return.
In estimatesUI(), when overlay=TRUE, the number of
lines in the resulting plot now reflects the number of unique dosing
values in data.
UNC paths are now supported, allowing RsNLME to be utilized with a shared directory inside a network drive.
c().An issue where stepwise covariate searches with criterion set to AIC could give incorrect results during backward elimination has been resolved (PHX-8226). Previously, for a stepwise covariate search run involving a multicore host and AIC, the page would use “+” instead of “-” for certain scenarios during the backward elimination.
For shotgun covariate searches, the total number of jobs/scenarios executed is set to 2^n, where n denotes the number of enabled covariate effects (DRWN-447).
An issue where using special words like ‘dose’, ‘obs’, ‘covr’ , and ‘mode’ could cause NLME to fail has been resolved (PHX-8024): In the previous version, using such special words as variables in the simulation table or as stratification variables would occasionally cause NLME to fail.
The issue of fraction excreted theta, used in urinecpt, being fixed irrespective of other statements has been resolved (PHX-8015).
An issue where having an overall number of fixed effects (including frozen and not enabled for the current scenario run) exceed the number of thetas + 100 could cause optimization to stop has been resolved (PHX-8020).
For non-time-based models with covariate effects, if the When covr set field contains a covariate that is not the last one defined in the Column Definition Text area, NLME no longer generates an incorrect execution error message that the covariate is not set (PHX-8199).
Using a sscol() statement in column definitions no longer creates
additional rows in the doses.csv file (PHX-8214).
The QRPEM engine now supports models in which the same thetas are used
in different stparm statements (PHX-8168).
In the calculation of steady state, when the DelayInfCpt statement is used and reset statements are present, the reset statements are now handled correctly (PHX-8013).
RsNLME 1.1.1 release corrects the issue where the posthoc table was missing if numIterations = 0 for model execution (RSNLME-2). The following files have been updated:
The updated version of Certara.NLME8 package v1.2.1 will
be automatically installed when performing
the installation for R packages. However, existing users should
request the updated NLME-Engine-21.11.2.
For Windows, after running NLME-Engine-21.11.2.exe you will first be prompted to remove the previous NLME-Engine installation. After removing NLME-Engine-21.11.1 via the installer, running NLME-Engine-21.11.2.exe once again will proceed with installing the updated version.
Linux users may simply extract contents of NLME-Engine-21.11.2.zip and replace their existing NLME_Engine folder with the updated version.
Note: While the version of the RsNLME software suite (R
packages and NLME-Engine) has been incremented to v1.1.1 for the above
hotfix, no changes have been made to the Certara.RSNLME
package and the version remains v1.1.0. Only the Certara.NLME8 R package
and NLME-Engine versions have been incremented.
New “type” argument for LL statements enables generation of appropriate summary statistics worksheets for VPC mode (PRN-652): In PML code, the type argument is now available for specifying an observation variable’s type. This argument can be set to cont, cat, count, or event and ensures the proper output worksheets will be generated for VPC mode.
Simple and Simulation tables include all five ID columns (PRN-645): NLME supports up to 5 ID columns for the input data. To take this into account, five ID columns are added for all simple and simulation tables.
New column ‘LLOQ’ is added to the output of predcheck output (PRN-726): To facilitate the computations of VPC data in R packages, the LLOQ column is added to the predcheck0.csv output file if the model has BQL observation data specified.
Additional steady state dosing can now be specified using the optional “SSOffset” argument of “addSteady” (PRN-317): This argument produces the “ssoffcol” statement in cols1.txt.
Columns mapped as covariates in the model object are now checked for validity (PRN-629): If data is loaded to a model object and covariate model terms are mapped to data columns, an automatic check is performed regarding data column reliability. A Warning/Error is given in cases where there is inappropriate data.
Initial Estimates Shiny application now uses ggplot2 (PRN-537): The estimatesUI initial estimates Shiny application in the Certara.RsNLME package has been updated to use the ggplot2 plotting library and to support plot faceting.
Command line support for the following has been added to the RsNLME package:
Distributed delay (PRN-618)
Supply class initializer arguments for execution params directly inside execution functions using ellipses (PRN-709)
Data mapping can now be performed without column mapping inside built-in model functions by supplying data argument and setting columnMap = FALSE (PRN-717).
Support for new syntax in mmdl:
Dosing cycles (PRN-633)
Covariate levels and labels (PRN-805)
Additional functionality has been added to the RsNLME.ModelBuilder Shiny application:
Administration-absorption parameters for distributed delay (PRN-773)
Dosing cycle specification (PRN-785)
Covariate labels (PRN-805)
Additional functionality has been added to the RsNLME.ModelExecutor Shiny application:
Plot convergence data after model execution (PRN-580)
Return estimation arguments and table statements to mmdl in Pirana (PRN-704)
Add sort column selections for model execution (PRN-423)
Additional information for Certara R packages that are accessed through Pirana is now available as pkgdown websites (PRN-838):
All interoccasion omegas have standard errors in the output (PRN-623): Previously, the output only contained the standard errors (SEs) for omegas related to the first occasion. Now, SEs are included for all interoccasion omegas.
An issue that prevented using more than five observation variables has been resolved (PRN-545): Previously, it was impossible to run a model with more than five observation variables using the QRPEM engine. This issue is fixed in RsNLME 1.1.
An issue involving the failure of parsing when more than one stratification variable is specified has been resolved (PRN-614).
Non-time-based models now work correctly (PRN-300): Previously, in a non-time-based model, if the name of a covariate in the model was the same as the corresponding one in the input dataset, the covariate would not be listed as a covariate in the database.
For models involving reset, the original dataset appended in the generated data is now correct (PRN-303): Previously, the generated data showed data for all occasions as being exactly the same as the ones corresponding to the first occasion.
Individual plot legends now properly display the line type and color (PRN-307).
Issue where column named “X_ID” in the data used as subject ID was incorrectly used for subjects accounting has been resolved (PRN-507).
A reported issue where executing a large NLME job on a grid led to the master node for the grid to run out of memory has been resolved (PRN-538).
NLME now accepts negative estimates as initial estimates for the model executed (PRN-543/CS00211446).
The NLME Engine installer must be run as an administrator or the installation will fail (RSNLME-346): If an error is encountered during installation, check that the person installing has administrator privileges.
NLME engine returns a negative value for the standard deviation of residual error variable (PRN-540): If such a situation occurs, then the absolute value of the standard deviation should be considered as the final estimate.