Parameters vs continuous covariates correlations

Returns a plot of the selected parameters and continuous covariates correlations.

plot_parameters_vs_continuous_covariates(run, parameters = NULL,
  covariates = NULL, type = "heatmap", correlation_method = NULL,
  auto_order = TRUE, baseline_only = TRUE, smoothing_method = NULL,
  smoothing_se = TRUE, fixed_ratio = TRUE, auto_legend = TRUE)

Arguments

run	pmxploit NONMEM run object.
parameters	character vector of parameters names. Default is NULL, returning all individual parameters (random and post-hoc).
covariates	character vector of continous covariates names. Default is NULL, returning all continuous covariates.
type	character. Type of distribution representation. One of histogram, density, boxplot and qq (Q-Q plot of the Normal distribution). Default is histogram.
correlation_method	a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated. If type = "scatterplot", "pearson" method will be used.
auto_order	logical. If type = "heatmap", auto-orders the matrix with respect to the distances between values. Default is TRUE.
baseline_only	logical. Consider only the baseline (= first) values of the subjects. Default is TRUE.
smoothing_method	character. If type = "scatterplot", corresponds to a ggplot2 smoothing method.
smoothing_se	logical. Display confidence interval around smooth?
fixed_ratio	logical. If type = "heatmap", plot scaled to a 1:1 ratio. Default is TRUE.
auto_legend	logical. When TRUE (default), default pmxploit plotting options are applied (title, labels, axis...).

Value

A ggplot2 object.

Examples

params <- c("ETCL", "ETV1", "KINT", "KDEG")
covs <- c("AGE", "WT", "BSLDLC", "FBSPCSK")

EXAMPLERUN %>%
  plot_parameters_vs_continuous_covariates(parameters = params, covariates = covs, type = "heatmap")+
  ggplot2::theme(legend.position = "bottom")

EXAMPLERUN %>%
  plot_parameters_vs_continuous_covariates(parameters = params, covariates = covs, type = "scatterplot", smoothing_method = "lm")
EXAMPLERUN %>%
  plot_parameters_vs_continuous_covariates(parameters = params, covariates = covs, type = "scatterplot", smoothing_method = "loess")
EXAMPLERUN %>%
  group_by(SEX) %>%
  plot_parameters_vs_continuous_covariates(parameters = params, covariates = covs, type = "scatterplot")