Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 7.2,
fig.height = 4,
warning = FALSE,
message = FALSE
)
options(rmarkdown.html_vignette.check_title = FALSE)
## ----setup, warning = FALSE, message = FALSE----------------------------------
# load packages
library(ggmice)
library(mice)
library(ggplot2)
# load incomplete dataset from mice
dat <- boys
# generate imputations
imp <- mice(dat, method = "pmm", printFlag = FALSE)
## ----bwplot-------------------------------------------------------------------
# original plot
mice::bwplot(imp, hgt ~ .imp)
# ggmice equivalent
ggmice(imp, aes(x = .imp, y = hgt)) +
geom_boxplot() +
labs(x = "Imputation number")
# extended reproduction with ggmice
ggmice(imp, aes(x = .imp, y = hgt)) +
stat_boxplot(geom = "errorbar", linetype = "dashed") +
geom_boxplot(outlier.colour = "grey", outlier.shape = 1) +
labs(x = "Imputation number") +
theme(legend.position = "none")
## ----densityplot--------------------------------------------------------------
# original plot
mice::densityplot(imp, ~hgt)
# ggmice equivalent
ggmice(imp, aes(x = hgt, group = .imp)) +
geom_density()
# extended reproduction with ggmice
ggmice(imp, aes(x = hgt, group = .imp, size = .where)) +
geom_density() +
scale_size_manual(
values = c("observed" = 1, "imputed" = 0.5),
guide = "none"
) +
theme(legend.position = "none")
## ----flux---------------------------------------------------------------------
# original plot
fluxplot(dat)
# ggmice equivalent
plot_flux(dat)
## ----md.pattern---------------------------------------------------------------
# original plot
md <- md.pattern(dat)
# ggmice equivalent
plot_pattern(dat)
# extended reproduction with ggmice
plot_pattern(dat, square = TRUE) +
theme(
legend.position = "none",
axis.title = element_blank(),
axis.title.x.top = element_blank(),
axis.title.y.right = element_blank()
)
## ----plot.mids----------------------------------------------------------------
# original plot
plot(imp, hgt ~ .it | .ms)
# ggmice equivalent
plot_trace(imp, "hgt")
## ----stripplot----------------------------------------------------------------
# original plot
mice::stripplot(imp, hgt ~ .imp)
# ggmice equivalent
ggmice(imp, aes(x = .imp, y = hgt)) +
geom_jitter(width = 0.25) +
labs(x = "Imputation number")
# extended reproduction with ggmice (not recommended)
ggmice(imp, aes(x = .imp, y = hgt)) +
geom_jitter(
shape = 1,
width = 0.1,
na.rm = TRUE,
data = data.frame(
hgt = dat$hgt,
.imp = factor(rep(1:imp$m, each = nrow(dat))),
.where = "observed"
)
) +
geom_jitter(shape = 1, width = 0.1) +
labs(x = "Imputation number") +
theme(legend.position = "none")
## -----------------------------------------------------------------------------
# original plot
mice::xyplot(imp, hgt ~ age)
# ggmice equivalent
ggmice(imp, aes(age, hgt)) +
geom_point()
# extended reproduction with ggmice
ggmice(imp, aes(age, hgt)) +
geom_point(size = 2, shape = 1) +
theme(legend.position = "none")
## ----plotly-------------------------------------------------------------------
# load packages
library(plotly)
# influx and outflux plot
p <- plot_flux(dat)
ggplotly(p)
## ----mapping------------------------------------------------------------------
# load packages
library(purrr)
library(patchwork)
# create vector with variable names
vrb <- names(dat)
## ----bwplots------------------------------------------------------------------
# original plot
mice::bwplot(imp)
# ggmice equivalent
p <- map(vrb, ~ {
ggmice(imp, aes(x = .imp, y = .data[[.x]])) +
geom_boxplot() +
scale_x_discrete(drop = FALSE) +
labs(x = "Imputation number")
})
wrap_plots(p, guides = "collect") &
theme(legend.position = "bottom")
## ----densityplots, message=FALSE, warning=FALSE-------------------------------
# original plot
mice::densityplot(imp)
# ggmice equivalent
p <- map(vrb, ~ {
ggmice(imp, aes(x = .data[[.x]], group = .imp)) +
geom_density()
})
wrap_plots(p, guides = "collect") &
theme(legend.position = "bottom")
## ----stripplots---------------------------------------------------------------
# original plot
mice::stripplot(imp)
# ggmice equivalent
p <- map(vrb, ~ {
ggmice(imp, aes(x = .imp, y = .data[[.x]])) +
geom_jitter() +
labs(x = "Imputation number")
})
wrap_plots(p, guides = "collect") &
theme(legend.position = "bottom")
## ----session, class.source = 'fold-hide'--------------------------------------
sessionInfo()
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.