plotRandomEffectsCorrelation

Usage

plotRandomEffectsCorrelation(
  parametersRows = NULL,
  parametersColumns = NULL,
  settings = list(),
  preferences = list(),
  stratify = list()
)

Arguments

parametersRows

vector with the name of parameters to display on rows (by default the first 4 computed parameters are displayed).

parametersColumns

vector with the name of parameters to display on columns (by default parametersColumns = parametersRows).

settings

List with the following settings

• indivEstimate Calculation of individual estimates: conditional mean ("mean"), conditional mode with EBE's ("mode"), conditional distribution ("simulated") (default "simulated").

• variabilityLevel (character) In case of IOV and if the conditional distribution is computed plot is displayed for one given level of variability (default NULL) If NULL, the variability level is ID + Occasions Run getVariabilityLevels() to see the available levels of variability

• decorrelated (logical) If TRUE, plot the decorrelated random effects instead of the random effects (default FALSE). Decorrelated random effects are available only if the model contains correlations terms between the random effects.

• regressionLine (logical) If TRUE, Add regression line in scatterplots (default TRUE).

• spline (logical) If TRUE, Add xpline in scatterplots (default FALSE).

• legend (logical) add (TRUE) / remove (FALSE) plot legend (default FALSE).

• grid (logical) add (TRUE) / remove (FALSE) plot grid (default TRUE).

• ncol (integer) number of columns when facet = TRUE (default 4).

• fontsize (integer) Plot text font size.

preferences

(optional) preferences for plot display, run getPlotPreferences("plotRandomEffectsCorrelation") to check available displays.

stratify

List with the stratification arguments:

• groups - Definition of stratification groups. By default, stratification groups are already defined as one group for each category for categorical covariates, and two groups of equal number of individuals for continuous covariates. To redefine groups, for each covariate to redefine, specify a list with:

  name	character	covariate name (e.g "AGE")
  definition	(vector(continuous) || list>(categorical))	For continuous covariates, vector of break values (e.g c(35, 65)). For categorical covariates, groups of categories as a list of vectors(e.g list(c("study101"), c("study201","study202")))

• split (vector) - Vector of covariates used to split (i.e facet) the plot (by default no split is applied). For instance c("FORM","AGE").

• filter (list< list> >) - List of pairs containing a covariate name and the vector of indexes or categories (for categorical covariates) of the groups to keep (by default no filtering is applied). For instance, list("AGE",c(1,3)) to keep the individuals belonging to the first and third age group, according to the definition in groups. For instance, list("FORM","ref") using the category name for categorical covariates.

• color (vector) - Vector of covariates used for coloring (by default no coloring is applied). For instance c("FORM","AGE").

• colors - Vector of colors to use when color argument is used. Takes precedence over colors defined in preferences. For instance c("#ebecf0","#cdced1","#97989c").

Value

• A ggplot object if one element in parametersRows and parametersColumns,

• A TableGrob object if multiple plots (output of grid.arrange)

See also

Examples

R

  initializeLixoftConnectors(software = "monolix")
  project <- file.path(getDemoPath(), "1.creating_and_using_models",
                       "1.1.libraries_of_models", "theophylline_project.mlxtran")
  loadProject(project)

  runPopulationParameterEstimation()
  runConditionalDistributionSampling()
  
  plotRandomEffectsCorrelation()

R

#> TableGrob (1 x 1) "arrange": 1 grobs
#>   z     cells    name            grob
#> 1 1 (1-1,1-1) arrange gtable[arrange]
  
  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               settings = list(indivEstimate = "simulated"))

R

  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               settings = list(spline = TRUE))    

R

  plotRandomEffectsCorrelation(settings = list(indivEstimate = "mean"))

R

#> TableGrob (1 x 1) "arrange": 1 grobs
#>   z     cells    name            grob
#> 1 1 (1-1,1-1) arrange gtable[arrange]
  plotRandomEffectsCorrelation(parametersRows = c("ka", "V"))

R

#> TableGrob (1 x 1) "arrange": 1 grobs
#>   z     cells    name            grob
#> 1 1 (1-1,1-1) arrange gtable[arrange]
  
  # stratification
  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               stratify = list(filter = list("SEX", "M")))

R

  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               stratify = list(color = "WEIGHT",
                                               groups = list(name = "WEIGHT", definition = 75),
                                               colors = c("#46B4AF", "#B4468A")))

R

  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               stratify = list(split = "SEX"))

R

                               
  plotRandomEffectsCorrelation(parametersRows = "ka", parametersColumns = "V",
                               stratify = list(split = c("SEX", "WEIGHT"),
                                               groups = list(name = "WEIGHT", definition = 70)))

R

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