View source: R/plot_parameters_vs_continuous_covariates.R
plot_parameters_vs_continuous_covariates | R Documentation |
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
)
run |
|
parameters |
character vector of parameters names. Default is |
covariates |
character vector of continous covariates names. Default is
|
type |
character. Type of distribution representation. One of
|
correlation_method |
a character string indicating which correlation
coefficient (or covariance) is to be computed. One of |
auto_order |
logical. If |
baseline_only |
logical. Consider only the baseline (= first) values of the subjects. Default is
|
smoothing_method |
character. If |
smoothing_se |
logical. Display confidence interval around smooth? |
fixed_ratio |
logical. If |
auto_legend |
logical. When |
A ggplot2 object.
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")
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