## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ---- warning = FALSE, eval = FALSE------------------------------------------- # dabest_plot( # dabest_effectsize_obj, # float_contrast = TRUE, # plot_component = "adjustment_value" # ) ## ---- warning = FALSE, 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() ## ---- warning = FALSE--------------------------------------------------------- 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 ) ## ---- warning = FALSE--------------------------------------------------------- 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!" ) ## ---- warning = FALSE--------------------------------------------------------- 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" ) ## ---- warning = FALSE--------------------------------------------------------- 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) ) ## ---- warning = FALSE--------------------------------------------------------- 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 ) ## ---- warning = FALSE--------------------------------------------------------- dabest_plot(dabest_paired_props.mean_diff, sankey = FALSE, raw_bar_width = 0.15) ## ---- warning = FALSE--------------------------------------------------------- dabest_plot(dabest_paired_props.mean_diff, flow = FALSE, raw_bar_width = 0.15) ## ---- warning = FALSE--------------------------------------------------------- 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 ) ## ---- warning = FALSE--------------------------------------------------------- dabest_plot(dabest_multigroup_obj.mean_diff, float_contrast = FALSE, show_baseline_ec = TRUE )