JointAI (version 1.0.2)

plot_imp_distr: Plot the distribution of observed and imputed values

Description

Plots densities and bar plots of the observed and imputed values in a long-format dataset (multiple imputed datasets stacked onto each other).

Usage

plot_imp_distr(data, imp = "Imputation_", id = ".id", rownr = ".rownr",
  ncol = NULL, nrow = NULL, labeller = NULL)

Arguments

data

a data.frame containing multiple imputations and the original incomplete data stacked onto each other

imp

the name of the variable specifying the imputation indicator

id

the name of the variable specifying the subject indicator

rownr

the name of a variable identifying which rows correspond to the same observation in the original (un-imputed) data

ncol

optional; number of columns in the plot layout; automatically chosen if unspecified

nrow

optional; number of rows in the plot layout; automatically chosen if unspecified

labeller

optional labeller to be passed to ggplot2::facet_wrap() to change the facet labels

Examples

# NOT RUN {
mod <- lme_imp(y ~ C1 + c2 + B2 + C2, random = ~ 1 | id, data = longDF,
               n.iter = 200, monitor_params = c(imps = TRUE), mess = FALSE)
impDF <- get_MIdat(mod, m = 5)
plot_imp_distr(impDF, id = "id", ncol = 3)

# }

Run the code above in your browser using DataCamp Workspace