In softloud/varameta: Estimators for the Variance of the Sample Median

knitr::opts_chunk$set(echo = TRUE)

library(ggraph)
library(tidygraph)
library(tidyverse)
library(hrbrthemes)

nodes_other_estimators <- tribble(
  ~object, ~type,
  "mean_est", "output",
  "mean_se_est", "output",
  "median", "input",
  "n", "input",
  "wan_mean_C1", "function",
  "min", "input",
  "max", "input",
  "wan_se_C1", "function",
  "q1", "input",
  "q3", "input",
  "wan_mean_C2", "function",
  "wan_se_C2", "function",
  "wan_mean_C3", "function",
  "wan_se_C3", "function",
  "hozo_mean", "function",
  "hozo_se", "function",
  "bland_mean", "function",
  "bland_se", "function"
) %>% 
  mutate(
    type = fct_relevel(type, "input", "function", "output")
  )

edges_other_estimators <- tribble(
  ~from, ~to,
  "min", "wan_mean_C1",
  "max", "wan_mean_C1",
  "median", "wan_mean_C1",
  "min", "wan_se_C1",
  "max", "wan_se_C1",
  "n", "wan_se_C1",
  "min", "wan_mean_C2",
  "q1", "wan_mean_C2",
  "median", "wan_mean_C2",
  "q3", "wan_mean_C2",
  "max", "wan_mean_C2",
  "min", "wan_se_C2",
  "q1", "wan_se_C2",
  "median", "wan_se_C2",
  "q3", "wan_se_C2",
  "max", "wan_se_C2",
  "n", "wan_se_C2",
  "wan_mean_C1", "mean_est",
  "wan_se_C1", "mean_se_est",
  "wan_mean_C2", "mean_est",
  "wan_se_C2", "mean_se_est",
  "q1", "wan_mean_C3",
  "median", "wan_mean_C3",
  "q3", "wan_mean_C3",
  "q1", "wan_se_C3",
  "median", "wan_se_C3",
  "q3", "wan_se_C3",
  "n", "wan_se_C3",
  "wan_mean_C3", "mean_est",
  "wan_se_C3", "mean_se_est",
  "min", "hozo_mean",
  "median", "hozo_mean",
  "max", "hozo_mean",
  "hozo_mean", "mean_est",
  "hozo_se", "mean_se_est",
  "min", "hozo_se",
  "median", "hozo_se",
  "max", "hozo_se",
  "n", "hozo_se",
  "min", "bland_mean",
  "q1", "bland_mean",
  "median", "bland_mean",
  "q3", "bland_mean",
  "max", "bland_mean",
  "min", "bland_se",
  "q1", "bland_se",
  "median", "bland_se",
  "q3", "bland_se",
  "max", "bland_se",
  "n", "bland_se",
  "bland_mean", "mean_est",
  "bland_se", "mean_se_est"
)

neets <- tribble(
  ~fn, ~one_neet, ~all_neets, ~and_the_rest,
  "effect_se", FALSE, FALSE, FALSE,
  "wan_mean_C1", FALSE, FALSE, FALSE
)

tbl_graph(nodes_other_estimators, edges_other_estimators) %>% 
  ggraph() +
  geom_edge_link(arrow = arrow(), colour = "lightgrey") + 
  geom_node_text(
    size = 3,
    aes(label = object, colour = type)
  ) + 
  scale_colour_ipsum() +
  coord_flip() +
  scale_y_reverse() +
  theme_graph() +
  theme(legend.position = "bottom")

variance of the sample median

nodes_medvar <- 
  tribble(
    ~object,~type,
    "effect_se", "fn",
    "g_lnorm", "fn",
    "g_cauchy", "fn",
    "g_norm", "fn",
    "g_exp", "fn",
    "iqr", "input",
    "range", "input",
    "median", "input",
    "n", "input",
    "median_se", "output"
  )

edges_medvar <- 
  tibble(
    from = c("n", "iqr", "range", "median") %>% rep(times = 4),
    to = c("effect_se", "g_lnorm", "g_cauchy", "g_norm") %>% rep(each = 4)
  ) %>% 
  bind_rows(
    tibble(
    from = c("n", "median"),
    to = rep("g_exp", times = 2)
    )
  ) %>% 
  bind_rows(
    tibble(
    from = c("effect_se", "g_lnorm", "g_cauchy", "g_norm", "g_exp"),
    to = rep("median_se")
    )
  )

tbl_graph(nodes_medvar, edges_medvar) %>% 
  ggraph() +
  geom_edge_link(arrow = arrow(), colour = "lightgrey") + 
  geom_node_text(
    size = 3,
    aes(label = object, colour = type)
  ) + 
  scale_colour_ipsum() +
  coord_flip() +
  scale_y_reverse() +
  theme_graph() +
  theme(legend.position = "bottom")