# Export charts data

### All plots generated by Monolix can be exported

All plots generated by Monolix can be exported as a figure or as text files in order to be able to plot it in another way or with other software for more flexibility.
All the files can be exported in R for example using the following command

 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.

The list of plots below corresponds to all the plots that Monolix can generate. They are computed with the task “Plots”, and the list of plots to compute can be selected by clicking on the button next to the task as shown below, prior to running the task.
Exporting the charts data can be made through the Export menu or through the preferences as described here.

In the following, we describe all the files generated by the export function

## Charts concerning the Data

### Observed data (continuous, categorical, and count)

#### xxx_observations.txt

Description: observation values

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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)

### Full output file description

 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)

### Full output file description

 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

### Full output file description

 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.

### Full output file description

 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.

### Full output file description

 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)

### Full output file description

 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

### Full output file description

 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)

### Full output file description

 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.

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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) – 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.

### Full output file description

 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)

### Full output file description

 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

### Visual Predictive Checks (discrete)

#### xxx_distribution.txt

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

### Full output file description

 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.

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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)

### Full output file description

 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.

### Full output file description

 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

### Full output file description

 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

### Full output file description

 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.

### Full output file description

 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

### Full output file description

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