如何将R生成的重复测量ANOVA结果整理导出为Word格式表格

前置依赖 #

先安装加载所需工具包：

# 未安装依赖时先执行安装
install.packages(c("flextable", "officer", "dplyr", "tidyr", "purrr", "ez"))
# 加载包
library(flextable)
library(officer)
library(dplyr)
library(tidyr)
library(purrr)
library(ez)

运行你提供的基础代码生成统计结果数据集：

# 数据集构造
df <- tibble::tibble(
  sensors = c("S_A", "S_B", "S_C", "T_A", "T_B", "T_C"),
  readings = list(
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = 0, sd = 1)
    ),
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = 1, sd = 2)
    ),
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = -1, sd = 1.5)
    ),
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = 2, sd = 0.5)
    ),
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = 0.5, sd = 1.2)
    ),
    tibble::tibble(
      subj = factor(rep(sprintf("P%02d", 1:5), each = 3)),
      cohort = factor(rep("G0", 15)),
      session = factor(rep("X1", 15)),
      phase = factor(rep(c("A1", "A2", "A3"), times = 5)),
      measurement = rnorm(15, mean = -0.5, sd = 0.8)
    )
  )
)

# ANOVA检验函数
fAddANOVA <- function(data) {   
  data %>%
    ez::ezANOVA(dv = .(measurement), wid = .(subj), within = .(phase)) %>%
    as_tibble() 
}

# 提取统计量
aov_stats <- df %>%
  dplyr::group_by(sensors) %>%
  dplyr::mutate(anova_output = purrr::map(readings, ~fAddANOVA(.x))) %>%
  dplyr::select(-readings) %>%
  tidyr::unnest(anova_output)

# 清理冗余空值列
aov_clean <- aov_stats %>% select(-where(~all(is.na(.))))

方案1：拆分生成3个独立表格 #

# 构造三个子表
## 表1：ANOVA核心测量指标
table1 <- aov_clean %>%
  select(sensors, Effect, DFn, DFd, SSn, SSd, F, `p`, `p<.05`)

## 表2：Mauchly球形检验结果
table2 <- aov_clean %>%
  select(sensors, Effect, Mauchly_W, Mauchly_p, `Mauchly_p<.05`) %>%
  filter(!is.na(Mauchly_W))

## 表3：球形校正后检验结果
table3 <- aov_clean %>%
  select(sensors, Effect, GGe, `p[GG]`, `p[GG]<.05`, HFe, `p[HF]`, `p[HF]<.05`) %>%
  filter(!is.na(GGe))

# 批量导出到Word
doc_split <- read_docx()
doc_split <- doc_split %>%
  body_add_par("表1 重复测量ANOVA核心结果", style = "heading 2") %>%
  body_add_flextable(flextable(table1) %>% theme_booktabs() %>% autofit()) %>%
  body_add_break() %>%
  body_add_par("表2 Mauchly球形检验结果", style = "heading 2") %>%
  body_add_flextable(flextable(table2) %>% theme_booktabs() %>% autofit()) %>%
  body_add_break() %>%
  body_add_par("表3 球形校正后ANOVA结果", style = "heading 2") %>%
  body_add_flextable(flextable(table3) %>% theme_booktabs() %>% autofit())

# 保存文件
print(doc_split, target = "ANOVA拆分结果.docx")

方案2：合并生成带分层表头的统一表格 #

# 构造合并表，去除冗余列
table_union <- aov_clean %>%
  select(
    sensors, Effect,
    DFn, DFd, SSn, SSd, F, `p`,
    Mauchly_W, Mauchly_p,
    GGe, `p[GG]`, HFe, `p[HF]`
  )

# 生成带分层表头的格式化表格
ft_union <- flextable(table_union) %>%
  # 添加分组表头
  add_header_row(
    top = TRUE,
    values = c("基础信息", "ANOVA核心结果", "Mauchly球形检验", "球形校正结果"),
    colwidths = c(2, 6, 2, 4)
  ) %>%
  # 格式美化
  theme_booktabs() %>%
  bold(part = "header") %>%
  align(align = "center", part = "all") %>%
  autofit()

# 导出到Word
doc_union <- read_docx()
doc_union <- doc_union %>%
  body_add_par("表 重复测量ANOVA完整检验结果", style = "heading 2") %>%
  body_add_flextable(ft_union)

# 保存文件
print(doc_union, target = "ANOVA合并结果.docx")

可选优化 #

• 可通过flextable的bg()函数将p值小于0.05的单元格标红，无需后续在Word中手动调整格式
• 若ezANOVA输出列名和示例不一致，直接调整select()中的列名即可适配

内容的提问来源于stack exchange，提问作者12666727b9