Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ---- eval = FALSE------------------------------------------------------------
# dabest_plot(
# dabest_effectsize_obj,
# float_contrast = TRUE,
# plot_component = "adjustment_value"
# )
## ---- include = FALSE---------------------------------------------------------
library(dabestr)
data(non_proportional_data)
data(proportional_data)
data(deltadelta_data)
dabest_twogroup_obj.mean_diff <- load(non_proportional_data, x = Group, y = Measurement, idx = c("Control 1", "Test 1")) %>%
mean_diff()
dabest_multigroup_obj.mean_diff <- load(non_proportional_data,
x = Group, y = Measurement,
idx = list(c("Control 1", "Test 1", "Test 2"), c("Control 2", "Test 3"))
) %>%
mean_diff()
dabest_unpaired_props.mean_diff <- load(proportional_data,
x = Group, y = Success,
idx = list(c("Control 1", "Test 1")),
proportional = TRUE
) %>%
mean_diff()
dabest_paired_props.mean_diff <- load(proportional_data,
x = Group, y = Success,
idx = list(c("Control 1", "Test 1", "Test 2", "Test 3"), c("Control 2", "Test 4")),
proportional = TRUE, paired = "sequential",
id_col = ID
) %>%
mean_diff()
## -----------------------------------------------------------------------------
dabest_plot(
dabest_twogroup_obj.mean_diff,
float_contrast = TRUE,
swarm_x_text = 30,
swarm_y_text = 1,
contrast_x_text = 30,
contrast_y_text = 5
)
## -----------------------------------------------------------------------------
dabest_plot(
dabest_twogroup_obj.mean_diff,
float_contrast = TRUE,
swarm_label = "I love estimation statistics.",
contrast_label = "I love it more than you do!"
)
## -----------------------------------------------------------------------------
A <- dabest_plot(dabest_twogroup_obj.mean_diff,
float_contrast = TRUE,
swarm_label = "", contrast_label = "",
raw_marker_size = 1, raw_marker_alpha = 1
)
B <- dabest_plot(dabest_twogroup_obj.mean_diff,
float_contrast = TRUE,
swarm_label = "", contrast_label = "",
raw_marker_size = 2, raw_marker_alpha = 0.5
)
cowplot::plot_grid(
plotlist = list(A, B),
nrow = 1,
ncol = 2,
labels = "AUTO"
)
## -----------------------------------------------------------------------------
dabest_plot(dabest_multigroup_obj.mean_diff,
float_contrast = FALSE,
contrast_label = "More negative is better!",
swarm_ylim = c(1, 5), contrast_ylim = c(0.7, -1.2)
)
## -----------------------------------------------------------------------------
npg <- dabest_plot(dabest_unpaired_props.mean_diff,
swarm_label = "", contrast_label = "",
custom_palette = "npg"
)
nejm <- dabest_plot(dabest_unpaired_props.mean_diff,
swarm_label = "", contrast_label = "",
custom_palette = "nejm"
)
jama <- dabest_plot(dabest_unpaired_props.mean_diff,
swarm_label = "", contrast_label = "",
custom_palette = "jama"
)
locuszoom <- dabest_plot(dabest_unpaired_props.mean_diff,
swarm_label = "", contrast_label = "",
custom_palette = "locuszoom"
)
cowplot::plot_grid(
plotlist = list(npg, nejm, jama, locuszoom),
nrow = 2,
ncol = 2
)
## -----------------------------------------------------------------------------
dabest_plot(dabest_paired_props.mean_diff, sankey = FALSE, raw_bar_width = 0.15)
## -----------------------------------------------------------------------------
dabest_plot(dabest_paired_props.mean_diff, flow = FALSE, raw_bar_width = 0.15)
## -----------------------------------------------------------------------------
right <- dabest_plot(dabest_twogroup_obj.mean_diff,
float_contrast = FALSE,
swarm_label = "", contrast_label = "",
asymmetric_side = "right"
)
left <- dabest_plot(dabest_twogroup_obj.mean_diff,
float_contrast = FALSE,
swarm_label = "", contrast_label = "",
asymmetric_side = "left"
)
cowplot::plot_grid(
plotlist = list(right, left),
nrow = 1,
ncol = 2
)
## -----------------------------------------------------------------------------
dabest_plot(dabest_multigroup_obj.mean_diff,
float_contrast = FALSE,
show_baseline_ec = TRUE
)
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.