R DEMO 認知・数理・情報分野方法論F1
初期設定
パッケージのインストール
# 第一回目ではコメントアウトして，パッケージをインストールする。
# install.packages("tidyverse")
# install.packages("rstatix")
# install.packages("ggpubr")パッケージの読み込み
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.0.5 ✓ dplyr 1.0.3
## ✓ tidyr 1.1.2 ✓ stringr 1.4.0
## ✓ readr 1.4.0 ✓ forcats 0.5.0## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(rstatix)##
## Attaching package: 'rstatix'## The following object is masked from 'package:stats':
##
## filterlibrary(ggpubr)データ
ToothGrowth (The Effect of Vitamin C on Tooth Growth in Guinea Pigs)
Description
The response is the length of odontoblasts (cells responsible for tooth growth) in 60 guinea pigs. Each animal received one of three dose levels of vitamin C (0.5, 1, and 2 mg/day) by one of two delivery methods, orange juice or ascorbic acid (a form of vitamin C and coded as VC).
3 (0.5, 1.0, 2.0) X 2 (VC, OJ) 被験者間 X 被験者間
データを確認する
data("ToothGrowth") # サンプルデータを読み込む
# dat <- read_csv() パソコンにあるデータを読み込む場合ToothGrowth## len supp dose
## 1 4.2 VC 0.5
## 2 11.5 VC 0.5
## 3 7.3 VC 0.5
## 4 5.8 VC 0.5
## 5 6.4 VC 0.5
## 6 10.0 VC 0.5
## 7 11.2 VC 0.5
## 8 11.2 VC 0.5
## 9 5.2 VC 0.5
## 10 7.0 VC 0.5
## 11 16.5 VC 1.0
## 12 16.5 VC 1.0
## 13 15.2 VC 1.0
## 14 17.3 VC 1.0
## 15 22.5 VC 1.0
## 16 17.3 VC 1.0
## 17 13.6 VC 1.0
## 18 14.5 VC 1.0
## 19 18.8 VC 1.0
## 20 15.5 VC 1.0
## 21 23.6 VC 2.0
## 22 18.5 VC 2.0
## 23 33.9 VC 2.0
## 24 25.5 VC 2.0
## 25 26.4 VC 2.0
## 26 32.5 VC 2.0
## 27 26.7 VC 2.0
## 28 21.5 VC 2.0
## 29 23.3 VC 2.0
## 30 29.5 VC 2.0
## 31 15.2 OJ 0.5
## 32 21.5 OJ 0.5
## 33 17.6 OJ 0.5
## 34 9.7 OJ 0.5
## 35 14.5 OJ 0.5
## 36 10.0 OJ 0.5
## 37 8.2 OJ 0.5
## 38 9.4 OJ 0.5
## 39 16.5 OJ 0.5
## 40 9.7 OJ 0.5
## 41 19.7 OJ 1.0
## 42 23.3 OJ 1.0
## 43 23.6 OJ 1.0
## 44 26.4 OJ 1.0
## 45 20.0 OJ 1.0
## 46 25.2 OJ 1.0
## 47 25.8 OJ 1.0
## 48 21.2 OJ 1.0
## 49 14.5 OJ 1.0
## 50 27.3 OJ 1.0
## 51 25.5 OJ 2.0
## 52 26.4 OJ 2.0
## 53 22.4 OJ 2.0
## 54 24.5 OJ 2.0
## 55 24.8 OJ 2.0
## 56 30.9 OJ 2.0
## 57 26.4 OJ 2.0
## 58 27.3 OJ 2.0
## 59 29.4 OJ 2.0
## 60 23.0 OJ 2.0長過ぎるので
head(ToothGrowth)## len supp dose
## 1 4.2 VC 0.5
## 2 11.5 VC 0.5
## 3 7.3 VC 0.5
## 4 5.8 VC 0.5
## 5 6.4 VC 0.5
## 6 10.0 VC 0.5データフレームの中身は、summary，もしくは str で確認できます。
summary(ToothGrowth)## len supp dose
## Min. : 4.20 OJ:30 Min. :0.500
## 1st Qu.:13.07 VC:30 1st Qu.:0.500
## Median :19.25 Median :1.000
## Mean :18.81 Mean :1.167
## 3rd Qu.:25.27 3rd Qu.:2.000
## Max. :33.90 Max. :2.000str(ToothGrowth)## 'data.frame': 60 obs. of 3 variables:
## $ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ...
## $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ...
## $ dose: num 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ...doseを要因に変換しないと
ToothGrowth$dose <- as.factor(ToothGrowth$dose)もう一回確認します
str(ToothGrowth)## 'data.frame': 60 obs. of 3 variables:
## $ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ...
## $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ...
## $ dose: Factor w/ 3 levels "0.5","1","2": 1 1 1 1 1 1 1 1 1 1 ...データの中身をさらに詳しく知りたい場合には
ToothGrowth %>%
group_by(dose, supp) %>%
get_summary_stats(len)## # A tibble: 6 x 15
## supp dose variable n min max median q1 q3 iqr mad mean
## <fct> <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 OJ 0.5 len 10 8.2 21.5 12.2 9.7 16.2 6.48 4.3 13.2
## 2 VC 0.5 len 10 4.2 11.5 7.15 5.95 10.9 4.95 3.56 7.98
## 3 OJ 1 len 10 14.5 27.3 23.4 20.3 25.6 5.35 3.93 22.7
## 4 VC 1 len 10 13.6 22.5 16.5 15.3 17.3 2.02 1.70 16.8
## 5 OJ 2 len 10 22.4 30.9 26.0 24.6 27.1 2.5 2.08 26.1
## 6 VC 2 len 10 18.5 33.9 26.0 23.4 28.8 5.42 4.60 26.1
## # … with 3 more variables: sd <dbl>, se <dbl>, ci <dbl>type = “mean_sd”を追加すると
ToothGrowth %>%
group_by(dose, supp) %>%
get_summary_stats(len, type = "mean_sd")## # A tibble: 6 x 6
## supp dose variable n mean sd
## <fct> <fct> <chr> <dbl> <dbl> <dbl>
## 1 OJ 0.5 len 10 13.2 4.46
## 2 VC 0.5 len 10 7.98 2.75
## 3 OJ 1 len 10 22.7 3.91
## 4 VC 1 len 10 16.8 2.52
## 5 OJ 2 len 10 26.1 2.66
## 6 VC 2 len 10 26.1 4.80Rで図を描く
Boxplots (or Box plots) are used to visualize the distribution of a grouped continuous variable through their quartiles.
Box Plots have the advantage of taking up less space compared to Histogram and Density plot. This is useful when comparing distributions between many groups.
Basic R
boxplot(ToothGrowth$len ~ ToothGrowth$dose)
GGplot2
Boxplot with multiple groups
e <- ggplot(ToothGrowth, aes(x = dose, y = len)) + geom_boxplot(aes(fill = supp))
e
Split into multiple panels
e + facet_wrap(~supp)
GGpubr
‘ggplot2’ Based Publication Ready Plots
ggboxplot(ToothGrowth, x = "dose", y = "len", color = "supp", add = "jitter")