Export charts data

All plots generated by Monolix can be exported

All plots generated by Monolix can be exported as figures or as text files in order to be able to plot them in another way or with other softwares for more flexibility.

Exporting the charts data can be made through the Export menu or through the preferences as described here.

The list of files in the next sections corresponds to all the charts data that Monolix can generate. They are computed with the task “Plots”, and the list of plots to compute in that task can be selected by clicking on the button next to the task prior to running it.

https://www.youtube.com/watch?v=JMyKwv9btbw

All the files can then be exported in R, for example using the following command:

CODE

 read.table("/path/to/file.txt", sep = ",", comment.char = "", header = T)

Remarks

The separator is the one defined in the user preferences. We set “,” in this example as it is the one by default.
The command comment.char = "" is needed for some files because to define groups or color, we use the character # that can be interpreted as a comment character by R.

Charts concerning the Data

Observed data (continuous, categorical, and count)

xxx_observations.txt

Description: observation values

Column	Description	Comment
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation time	–
y	Observation value (loq)	The name of the column is the observation name
censored	1 if the observation is censored, 0 otherwise	–
split	Name of the split the subject belongs to	–
color	Name of the color the observation is colored with	–
filter	1 if the subject is filtered, 0 otherwise	–

Observed data (event)

xxx_curves.txt

Description: observation values

Column	Description	Needed Task
time	Observation times	–
survivalFunction	Survival of first event	–
averageEventNumber	Average number of event at that time	–
split	Name of the split the subject occasion belongs to	–

xxx_censored.txt

Description: censored values

Column	Description	Needed Task
time	Observation times	–
values	Survival of first event	–
split	Name of the split the subject occasion belongs to	–

Model for the observations

Individual Fits

xxx_observations.txt

Description: observation values

Column	Description	Comment
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation time	–
y	Observation value (loq)	–
median	Prediction interval median	–
piLower	Lower percentile of the individual prediction interval	–
piUpper	Upper percentile of the individual prediction interval	–
censored	1 if the observation is censored, 0 otherwise	–

xxx_fits.txt

Description: individual fits based on population parameters and individual parameters

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Continuous time grid used to compute fits	–
pop	Prediction using population parameter values and average covariate value from the population (continuous) or reference covariate value (categorical).	–
popPred	Prediction using population parameter values and individual covariates.	–
indivPredMean	Prediction based on the individual parameter values estimated by conditional mean	Conditional distribution need to be computed
indivPredMode	Prediction based on the individual parameter values estimated by conditional mode	EBEs need to be computed

Observation vs Prediction

xxx_obsVsPred.txt

Description: observation and prediction (pop & indiv) values

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	time of the observation
y	Observation value (loq)	–
y_simBlq	Observation value (simulated blq)
popPred	Predictions based on population parameter values
indivPredMean	Predictions based on the individual parameter values estimated by conditional mean	Conditional distribution need to be computed
indivPredMode	Predictions based on the individual parameter values estimated by conditional mode	EBEs need to be computed
censored	1 if the observation is censored, 0 otherwise
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

xxx_obsVsSimulatedPred.txt

Description: observation and simulated prediction values

Column	Description	Needed Task
rep	Replicate id
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	time of the observation
y	Observation value (loq)	–
y_simBlq	Observation value (simulated blq)
indivPredSimulated	Predictions based on the simulated individual parameter values estimated by conditional distribution	Conditional distribution need to be computed
censored	1 if the observation is censored, 0 otherwise
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise

xxx_visualGuides.txt

Description: splines and confidence intervals for predictions

Column	Description	Needed Task
popPred	Continuous grid over population prediction values	–
popPred_spline	Spline ordinates for population predictions	–
popPred_piLower	Lower percentile of prediction interval for population predictions	–
popPred_piUpper	Upper percentile of prediction interval for population predictions	–
indivPred	Continuous grid over individual prediction values	–
indivPred_spline	Spline ordinates for individual predictions	–
indivPred_piLower	Lower percentile of prediction interval for individual predictions	–
indivPred_piUpper	Upper percentile of prediction interval for individual predictions	–
split	Name of the split the visual guides belong to

Distribution of the residuals

xxx_pdf.txt

Description: probability density function of each residual type (pwres, iwres, npde)

Column	Description	Needed Task
pwRes_abscissa	Abscissa for pwres pdf	–
pwRes_pdf	Pdf of pwres	–
iwRes_abscissa	Abscissa for iwres pdf	–
iwRes_pdf	Pdf of the iwres	–
npde_abscissa	Abscissa for npde pdf	–
npde_pdf	Pdf of the npde	–
split	–

xxx_cdf.txt

Description: cumulative distribution function of each residual type (pwres, iwres, npde)

Column	Description	Needed Task
pwRes_abscissa	Abscissa for pwres cdf	–
pwRes_cdf	Cdf of pwres	–
iwRes_abscissa	Abscissa for iwres cdf	–
iwRes_cdf	Cdf of the iwres	–
npde_abscissa	Abscissa for npde cdf	–
npde_cdf	Cdf of the npde	–
split	–

theoreticalGuides.txt

Description: theoretical guides for the pdf and the cdf

Column	Description	Needed Task
abscissa,pdf,cdf	Abscissa for the theoretical curves	–
pdf	Theoretical value of the pdf	–
cdf	Theoretical value of the cdf	–

Scatter plot of the residuals

xxx_prediction_percentiles_iwRes.txt

Description: prediction percentiles of the iwREs to plot iwRes w.r.t. the prediction. The same files exists with the pwres and the npde.

Column	Description	Needed Task
prediction	Value of the prediction	–
empirical_median	Empirical median of the iwRes	–
empirical_lower	Empirical lower percentile of the iwRes
empirical_upper	Empirical upper percentile of the iwRes
theoretical_median	Theoretical median of the iwRes
theoretical_lower	Theoretical lower of the iwRes
theoretical_upper	Theoretical upper of the iwRes
theoretical_median_piLower	Lower bound of the theoretical median prediction interval
theoretical_median_piUpper	Upper bound of the theoretical median prediction interval
theoretical_lower_piLower	Lower bound of the theoretical lower prediction interval
theoretical_lower_piUpper	Upper bound of the theoretical lower prediction interval
theoretical_upper_piLower	Lower bound of the theoretical upper prediction interval
theoretical_upper_piUpper	Upper bound of the theoretical upper prediction interval
split	Name of the split the subject occasion belongs to

xxx_time_percentiles_iwRes.txt

Description: time percentiles of the iwREs to plot iwRes w.r.t. the time. The same files exists with the pwres and the npde.

Column	Description	Needed Task
time	Value of the time	–
empirical_median	Empirical median of the iwRes	–
empirical_lower	Empirical lower percentile of the iwRes
empirical_upper	Empirical upper percentile of the iwRes
theoretical_median	Theoretical median of the iwRes
theoretical_lower	Theoretical lower of the iwRes
theoretical_upper	Theoretical upper of the iwRes
theoretical_median_piLower	Lower bound of the theoretical median prediction interval
theoretical_median_piUpper	Upper bound of the theoretical median prediction interval
theoretical_lower_piLower	Lower bound of the theoretical lower prediction interval
theoretical_lower_piUpper	Upper bound of the theoretical lower prediction interval
theoretical_upper_piLower	Lower bound of the theoretical upper prediction interval
theoretical_upper_piUpper	Upper bound of the theoretical upper prediction interval
split	Name of the split the subject occasion belongs to

xxx_residuals.txt

Description: residuals values (pwres, iwres, npde)

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation times	–
prediction_pwRes	Predictions based on population parameter values	SAEM
pwRes	PwRes (computed with observations)	SAEM
pwRes_blq	PwRes (computed with simulated blq)
prediction_iwRes_mean	Predictions based on the individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either
iwRes_mean	IwRes (computed with observations and individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either)
iwRes_mean_simBlq	IwRes (computed with simulated blq and individual parameter values estimated by conditional mean (INDIVESTIM) if available, SAEM either)
prediction_iwRes_mode	Predictions based on the individual parameter values estimated by conditional mode (INDIVESTIM)
iwRes_mode	IwRes (computed with observations and the individual parameter values estimated by conditional mode (INDIVESTIM))
iwRes_mean_simBlq	IwRes (computed with simulated blq and the individual parameter values estimated by conditional mode (INDIVESTIM))
prediction_npde	Predictions based on population parameter values
npde	Npde (computed with observations)
npde_simBlq	Npde (computed with simulated blq)	SAEM – If there are some censored data in the data set
censored	1 if the observation is censored, 0 otherwise
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

xxx_simulatedResiduals.txt

Description: simulated residuals values

Column	Description	Needed Task
rep	replicate	–
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation times	–
prediction_iwRes	Predictions based on the simulated individual parameter values based on the conditional distribution
iwRes_simulated	IwRes (computed with observations and the simulated individual parameter values)
iwRes_simulated_simBlq	IwRes (computed with simulated blq and the simulated individual parameter values)
censored	1 if the observation is censored, 0 otherwise	–
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

xxx_spline.txt

Description: splines (residuals values against time and prediction)

Column	Description	Needed Task
time_pwRes	Time grid for pwRes spline	SAEM
time_pwRes_spline	pwRes against time spline	SAEM
time_iwRes	Time grid for iwRes spline	At least SAEM
time_iwRes_spline	iwRes against time spline	At least SAEM
time_npde	Time grid for npde spline	SAEM
time_npde_spline	npde against time spline	SAEM
prediction_pwRes	Prediction grid for pwRes spline	SAEM
prediction_pwRes_spline	pwRes against population prediction spline	SAEM
prediction_iwRes	Prediction grid for iwRes spline	At least SAEM
prediction_iwRes_spline	iwRes against individual prediction spline	At least SAEM
prediction_npde	Prediction grid for npde spline	SAEM
prediction_npde_npde	npde against population prediction spline	SAEM
split	Name of the split the visual guides belong to	If the chart is splitted

xxx_{time,population,individual}Bins.txt

Description: bins values for the corresponding axis.

Column	Description	Needed Task
binsValues	Abscissa bins values	–
split	Name of the split the bins refer to	If the chart is splitted

Model for the individual parameters

Distribution of the individual parameters

cdf.txt

Column	Description	Needed Task
param_abscissa	Abscissa of the cdf of the individual parameter param	–
param_cdf	Empirical cdf of the individual parameter param	–
split	Name of the split the subject occasion belongs to

pdf.txt

Column	Description	Needed Task
param_abscissa	Abscissa of the pdf of the individual parameter param	–
param_pdf	Empirical pdf of the individual parameter param	–
split	Name of the split the subject occasion belongs to

visualGuides.txt

Column	Description	Needed Task
param_abscissa	Abscissa of the pdf and the pdf of the individual parameter param	–
param_pdf	Theoretical pdf of the individual parameter param	–
param_cdf	Theoretical cdf of the individual parameter param

Distribution of the random effects

cdf.txt

Column	Description	Needed Task
param_abscissa	Abscissa of the cdf of the standardized random effect of param	–
param_cdf	Empirical cdf of the standardized random effect of param	–
split	Name of the split the subject occasion belongs to

pdf.txt

Column	Description	Needed Task
param_abscissa	Abscissa of the pdf of the standardized random effect of param	–
param_pdf	Empirical pdf of the standardized random effect of param	–
split	Name of the split the subject occasion belongs to

StandardizedEta.txt

Description: standardized random effects of the individual parameters

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
standEta_X_method	Standardized random effects values on each individual parameter with variability. It can be StandEta_SAEM, StandEta_Mean, StandEta_Mode	–
filter	1 if the subject is filtered, 0 otherwise	–

SimulatedStandardizedEta.txt

Description: simulated standardized random effects of the individual parameters

Column	Description	Needed Task
rep	Replicate id	–
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
standEta_X_simulated	Standardized random effects values on each individual parameter with variability.	–
filter	1 if the subject is filtered, 0 otherwise	–

Correlation between Random Effects

eta.txt

Description: standard error on individual parameter predictions

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
eta_X_method	Random effects values on each individual parameter with variability. It can be eta_SAEM, eta_Mean, or eta_Mode	–
color	Name of the color the ID is colored with	–
filter	1 if the subject is filtered, 0 otherwise	–

simulatedEta.txt

Description: standard error on individual parameter predictions

Column	Description	Needed Task
rep	Replicate number
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
eta_X_simulated	Simulated random effects values on each individual parameter	–
color	Name of the color the ID is colored with	–
filter	1 if the subject is filtered, 0 otherwise	–

visualGuides.txt

Description: spline and linear regression for each couple of individual parameters plotted one against the other

This is done for each combination of parameter p1 and p2 to have p1 w.r.t. p2

Column	Description	Needed Task
p1_vs_p2_abscissa	Abscissa	–
p1_vs_p2_spline	Spline ordinates	–
p1_vs_p2_regression	Linear regression ordinates	–

Individual Parameters Vs Covariates

covariates.txt

Description: individual parameters and random effects and covariate value for each subject

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
trans_X_method	Individual parameter value in the transformed space. It can be X_SAEM, X_mean, or X_mode	–
eta_X_method	Random effects values. It can be eta_X_SAEM, eta_Mean, or eta_Mode	–
covariate	Covariates values
split
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise

simulatedCovariates.txt

Description: simulated individual parameters and random effects and covariate value for each subject

Column	Description	Needed Task
rep	Replicate of the simulation
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
trans_X_simulated	Simulated transformed individual parameter value.	–
eta_X_simulated	Simulated random effects values.	–
covariate	Covariates values
split
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

visualGuides.txt

Description: spline and linear regression for each couple of individual parameters plotted against a covariate

This is done for each combination of parameter param and covariate cov to have param w.r.t. cov

Column	Description	Needed Task
param_vs_cov_abscissa	Abscissa	–
param_vs_cov_spline	Spline ordinates	–
param_vs_cov_regression	Linear regression ordinates	–

Predictive checks and prediction

Visual Predictive Checks (continuous)

xxx_observations.txt

Description: observation values

Column	Description	Needed Task
ID	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation times	–
timeAfterLastDose	Observation times after the last dose	–
y	Observation values (loq)	–
y_simBlq	Observation values (simulated blq)
censored	1 if the observation is censored, 0 otherwise	–
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

xxx_bins.txt

Description: bins values for the corresponding axis.

Column	Description	Needed Task
binsValues	Abscissa bins values	–
split	Name of the split the bins refer to	If the chart is splitted

xxx_percentiles.txt

Description: empirical and theoretical percentiles values (lower, median & upper) + confidence interval on theoretical percentiles (lower & upper)

Column	Description	Needed Task
bins_middles	Abscissa bin middles	–
empirical_median	Empirical median	–
empirical_lowerPercentile	Empirical lower percentile	–
empirical_upperPercentile	Empirical upper percentile	–
theoretical_median	Theoretical median	–
theoretical_median_piLower	Lower percentile of prediction interval of theoretical median	–
theoretical_median_piUpper	Upper percentile of prediction interval of theoretical median	–
theoretical_lowerPercentile	Median of the prediction interval for the lower percentile	–
theoretical_lower_piLower	Lower percentile of the prediction interval for the lower percentile	–
theoretical_lower_piUpper	Upper percentile of the prediction interval for the lower percentile	–
theoretical_upperPercentile	median of the prediction interval for the upper percentile	–
theoretical_upper_piLower	Lower percentile of the prediction interval for the upper percentile	–
theoretical_upper_piUpper	Upper percentile of the prediction interval for the upper percentile	–
split	Name of the split the visual guides belong to	If the chart is splitted

xxx_simulations.txt

Description: simulated values. This file is not exported by default with the charts data, but it can be exported by clicking on “Export > Export VPC simulations” in the application menu. Moreover, if the option “Export VPC simulations” is enabled in the Preferences, it is exported each time the VPC is generated.

Column	Description	Needed Task
rep	Simulation replicate	–
ID	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time / timeAfterLastDose	Observation times or times after last dose	timeAfterLastDose if the corresponding option is used in the VPC
sim_y	Simulated observation values (loq)	–
censored	1 if the observation is censored, 0 otherwise	–
split	Name of the split the subject occasion belongs to
	color	Name of the color the observation is colored with
filter	1 if the subject is filtered, 0 otherwise	–

Visual Predictive Checks (discrete)

xxx_distribution.txt

Description: discrete observation modalities theoretical distribution (among continuous time grid)

Column	Description	Needed Task
binsTimeBefore	Abscissa bins time value before this time	–
binsTimeAfter	Abscissa bins time value after this time
propCategory_empirical	Empirical proportion of the modality set represented by the subchart	–
propCategory_median	Median of the prediction interval for the proportion of the modality set represented by the subchart	–
propCategory_piLower	Lower percentile of the prediction interval for proportion of the modality set represented by the subchart	–
propCategory_piUpper	Upper percentile of the prediction interval for proportion of the modality set represented by the subchart	–
category	Label for modality sets
split	Name of the split the distributions refer to	–

xxx_xBins.txt

Description: bins values for the x-axis.

Column	Description	Needed Task
binsValues	Abscissa bins values	–
split	Name of the split the bins refer to	If the chart is splitted

Visual Predictive Checks (event)

xxx_curves.txt

Description: observation values

Column	Description	Needed Task
time	Observation times	–
survivalFunction_empirical	Empirical survival of first event	–
survivalFunction_median	Survival median
survivalFunction_pXX	Survival percentile XX
averageEventNumber_empirical	Empirical mean number of events	–
averageEventNumber_median	Median mean number of events
averageEventNumber_pXX	Percentile XX mean number of events
split	Name of the split the subject occasion belongs to	If the chart is splitted

xxx_censored.txt

Description: censored values

Column	Description	Needed Task
time	Observation times	–
values	Survival of first event	–
split	Name of the split the subject occasion belongs to	–

BLQ Predictive Checks

xxx_cumulatedBLQfrequencies.txt

Description: censored simulated observations cumulated frequency

Column	Description	Needed Task
time	Time	–
empiricalCumulatedFrequencies	Empirical fraction of data that is BLQ between time 0 and time t	–
median	Prediction interval median	–
piLower	Lower bound of prediction interval	–
piUpper	Upper bound of prediction interval	–
split	Name of the split the visual guides belong to

Numerical Predictive Check

xxx_cdf.txt

Description: empirical and theoretical cumulative distribution function of observations

Column	Description	Needed Task
time	Cdf continuous grid time	–
empiricalCdf	Empirical cdf based on observations	–
theoreticalCdf	Median of prediction interval for cdf	–
piLower	Lower percentile of prediction interval for cdf	–
piUpper	Upper percentile of prediction interval for cdf	–
split	Name of the split the visual guides belong to

Prediction distribution (continuous)

xxx_observations.txt

Description: observation values

Column	Description	Needed Task
id	Subject identifier	–
OCC	Occasion value	(optional) if there is IOV in the data set
time	Observation times	–
y	Observation values (loq)	–
censored	1 if the observation is censored, 0 otherwise	–
split	Name of the split the subject occasion belongs to
color	Name of the color the observation is colored with
filter	1 if the subject occasion is filtered, 0 otherwise

xxx_percentiles.txt

Description: theoretical percentiles computed on continuous grid

Column	Description	Needed Task
time	Continuous time grid used for simulation	–
median	Median	–
pPercentile	Percentile	–
split	Name of the split the visual guides belong to	If the chart is splitted

Prediction distribution (discrete)

xxx_distribution.txt

Description: discrete observation modalities theoretical distribution (among continuous time grid)

Column	Description	Needed Task
binsTimeBefore	Abscissa bins time value before this time	–
binsTimeAfter	Abscissa bins time value after this time
propCategory_empirical	Empirical proportion of the modality set represented by the subchart	–
propCategory_median	Median of the prediction interval for the proportion of the modality set represented by the subchart	–
propCategory_piLower	Lower percentile of the prediction interval for proportion of the modality set represented by the subchart	–
propCategory_piUpper	Upper percentile of the prediction interval for proportion of the modality set represented by the subchart	–
category	Label for modality sets
split	Name of the split the distributions refer to	–

xxx_xBins.txt

Description: bins values for the x-axis.

Column	Description	Needed Task
binsValues	Abscissa bins values	–
split	Name of the split the bins refer to	If the chart is splitted

Convergence diagnosis

SAEM

CvParam.txt

Description: evolution of the parameters during SAEM iterations

Column	Description	Needed Task
iteration	Iteration number	–
convergenceIndicator	Convergence Indicator	–
phase	1 for exploratory and 2 for smoothing
X	Parameter X	–

MCMC

convergences.txt

Description: evolution of the convergence with respect to the MCMC iterations

Column	Description	Needed Task
iteration	Iteration number	–
E_X	Conditional expectation of the parameter X	–
sd_X	Conditional standard error of the parameter X

bounds.txt

Description: bounds for each parameter corresponding to the bounds on the graph. The first line corresponds to the minimum and the second one corresponds to the maximum.

Column	Description	Needed Task
E_X	Conditional expectation of the parameter X	–
sd_X	Conditional standard error of the parameter X

Standard errors of the estimates

rse.txt

Description: Standards errors for each parameter

Column	Description	Needed Task
X	parameter	–
rse_lin	Relative standard error with linearization method	–
rse_sa	Relative standard error with linearization method