R4Psy/chapter6_practice_new.Rmd at main · GuoJunyuKoi/R4Psy · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
---
title: "修改"
output:
   xaringan::moon_reader:
    css: [default, css/Font_Style.css]
    lib_dir: libs
    nature:
      highlightStyle: github
      highlightLines: true
      countIncrementalSlides: false
date: "2025-03-24"
---
<!-- ##### -->
<!-- ##### -->
<!-- 之前这个练习的操作重复了 -->
<!-- ##### -->
<!-- ##### -->

# <h1 lang="en">6.1 Tidyverse</h1>
<span style="font-size: 30px;">小练习</span></center><br>

- 请基于tidyverse的管道操作符合并下面三段代码，省去中间变量
```{r, task1}
# 创建dataframe
data <- data.frame(
  "grammer" = c("R","SPSS","Python","R",NA,"Matlab","Python","R"),
  "score" = c(4,2,5,4.5,5,4,2,5),
  "popularity" = c(1,2,NA,4,5,6,7,10)
  )
# 提取含字符串"R"的行
filtered_data <- data[data$grammer == 'R', ]
# 按照“popularity”进行排序
arranged_data <- filtered_data[order(factor(filtered_data$poplarity)),]

```

- 提示
```{r, message=FALSE}
# 不要忘记加载包
library(tidyverse)

# 补全下列代码,可以使用刚刚举例的filter()和arrange()函数
# arranged_data <- data %>%
```

---
# <h1 lang="en">6.3 反应时数据</h1>
<span style="font-size: 30px;">练习</span></center><br>

计算不同Shape情况下(immoralself，moralself，immoralother，moralother)<br>
基于信号检测论match与mismatch(match为信号，mismatch噪音)之间的d'<br>

提示：<br>
- 1 $d′$ = ${Z_{击中率}−Z_{虚报率}}$ = $\frac{M_{SN}-M_N}{\sigma_N}$ <br><br>
- 2 $击中率$ = $\frac{击中次数}{信号总次数}$ <br><br>
- 3 $虚报率$ = $\frac{虚报次数}{噪音总次数}$
<br>

---
- 1 以下是计算击中(hit)、虚报(fa)、漏报(miss)和正确否定(cr)的代码<br>
```{r, 6.3_prec, eval=FALSE}
# 去掉下面#的部分，将***替换成合适的变量，补全代码
dplyr::summarise(
      # *** = length(ACC[Match == "match" & ACC == 1]),
      # *** = length(ACC[Match == "mismatch" & ACC == 0]),
      # *** = length(ACC[Match == "match" & ACC == 0]),
      # *** = length(ACC[Match == "mismatch" & ACC == 1]),
```
- 2 以下是计算 $d′$ 的代码<br>
```{r, 6.3_prec2, eval=FALSE}
        Dprime = qnorm(
        ifelse(hit / (hit + miss) < 1,
               hit / (hit + miss),
               1 - 1 / (2 * (hit + miss))
              )
        )
             - qnorm(
        ifelse(fa / (fa + cr) > 0,
              fa / (fa + cr),
              1 / (2 * (fa + cr))
              )
                    )
      )
```
---
# <h1 lang="en">6.3 反应时数据</h1>
<span style="font-size: 30px;">6.3.3 小结</span></center><br>
- **练习思路**<br>
<br>
Step1: 选择需要的变量 <br>
<br>
Step2: 基于Sub, Shape分组[extract,filter] <br>
<br>
Step3: 使用计算公式，计算d值 <br>
<br>
Step4: 删除击中、虚报、误报、正确拒绝 <br>
<br>
Step5: 长转宽，得到每个Shape情况下的信号检测论d值[pivot_wide] <br>


---
# <h1 lang="en">6.3 反应时数据</h1>
<span style="font-size: 30px;">6.3.3 小结</span></center><br>
- **答案参考**<br>
<br>
<img src="./picture/chp6/answer.png" width="100%" style="display: block; margin-left: auto; margin-right: auto;">