Result Plot

Forward method using confidence intervels

Loading data

library(ggplot2)
library(plotly)
library(dplyr)

Data wrangling

dta <- read.csv("result.csv", header = T)
dta$condition <-
  factor(
    dta$condition,
    levels = c(
      "small_difference",
      "large_difference",
      "mixed_difference",
      "nonuniform_difference"
    ),
    labels = c(
      "small_difference",
      "large_difference",
      "mixed_difference",
      "nonuniform_difference"
    )
  )

dta$sample_size <-
  factor(
    dta$sample_size,
    levels = c("250", "500", "1000"),
    labels = c("250", "500", "1000")
  )

dta$confidence_intervel <-
  factor(
    dta$confidence_intervel,
    levels = c("0.95", "0.99"),
    labels = c("0.95", "0.99")
  )

Perfect rate plot

p1 <- dta %>% ggplot(aes(x = condition,
                         y = perfect_rate,
                         group = sample_size)) +
  geom_point(aes(shape = sample_size),
             size = 2,
             fill = "red") +
  geom_line(aes(linetype = sample_size)) +
  facet_grid(rows  = vars(confidence_intervel))
ggplotly(p1)

## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

Type I error rate plot

p2 <- dta %>% ggplot(aes(x = condition,
                         y = typei_rate,
                         group = sample_size)) +
  geom_point(aes(shape = sample_size),
             size = 2,
             fill = "red") +
  geom_line(aes(linetype = sample_size)) +
  facet_grid(rows  = vars(confidence_intervel))
ggplotly(p2)

Type II error rate

p3 <- dta %>% ggplot(aes(x = condition,
                         y = typeii_rate,
                         group = sample_size)) +
  geom_point(aes(shape = sample_size),
             size = 2,
             fill = "red") +
  geom_line(aes(linetype = sample_size)) +
  facet_grid(rows  = vars(confidence_intervel))
ggplotly(p3)