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在一个rmarkdown文档中，我正在创建一个包含标准误差的回归系数的 Latex 表，以比较单个表中的多个回归模型。我想垂直对齐每个模型的系数，以便系数的小数点垂直排列在一列。

我texreg用来创建表。默认情况下，系数不是小数对齐的（相反，每个字符串都在其列中居中），我正在寻找一种方法来让系数小数对齐。我不喜欢texreg，所以如果您有使用 , 或任何其他方法的解决方案xtable，pander我stargazer也会对此感兴趣。理想情况下，我想要一个可以在文档中以编程方式实现的解决方案，而不是在将文档呈现为文件后rmarkdown调整标记。latex.tex

作为奖励，我还希望能够在表格标题中放置换行符。例如，texreg您可以使用custom.model.names参数为每个回归模型设置列名。在下面的示例中，我想"Add Horsepower and AM"分成两行，这样列就不需要那么宽了。我试过"Add Horsepower \newline and AM"了，但这只是在最后的列标题中添加了“ewline”，而“\n”被忽略了。

这是一个可重现的示例：

---
title: "Regression Table"
author: "eipi10"
date: "August 15, 2016"
header-includes:
    - \usepackage{dcolumn}
output: pdf_document
---

```{r, echo=FALSE, message=FALSE, results="asis"}
library(texreg)

m1 = glm(mpg ~ wt + factor(cyl), data=mtcars)
m2 = glm(mpg ~ wt + factor(cyl) + hp + factor(am), data=mtcars)

texreg(list(m1,m2),
       single.row=TRUE, 
       custom.model.names=c("Base Model", "Add Horsepower and AM"),
       custom.coef.names=c("Intercept", "Weight","Cyl: 6", "Cyl: 8", "Horsepower","AM: 1"))
```

这是输出表的样子：

在此处输入图像描述

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2 回答 2

1

这需要相当多的争论，但我认为它可以让你接近你想要的。我用过xtable。主要思想是为每个模型创建两列，一列右对齐（系数），另一列左对齐（标准误差）。所以对于一个有两个模型的表，我们有五列。标题和汇总统计信息显示在跨两列的单元格中。

首先，我们有，在pheader.tex上绘图。27xtable个小插曲：

\usepackage{array}
\usepackage{tabularx}
\newcolumntype{L}[1]{>{\raggedright\let\newline\\
\arraybackslash\hspace{0pt}}m{#1}}
\newcolumntype{C}[1]{>{\centering\let\newline\\
\arraybackslash\hspace{0pt}}m{#1}}
\newcolumntype{R}[1]{>{\raggedleft\let\newline\\
\arraybackslash\hspace{0pt}}m{#1}}
\newcolumntype{P}[1]{>{\raggedright\tabularxbackslash}p{#1}}

该.Rmd文件。add.to.row我从这个答案中了解到。

---
title: "Regression Table"
author: "eipi10"
date: "August 15, 2016"
header-includes:
    - \usepackage{dcolumn}
output: 
  pdf_document:
    includes:
      in_header: header.tex
---

```{r, echo=FALSE, message=FALSE, results="asis"}
library(xtable)
library(broom)   

m1 = glm(mpg ~ wt + factor(cyl), data=mtcars)
m2 = glm(mpg ~ wt + factor(cyl) + hp + factor(am), data=mtcars)

p_val <- c(0, 0.001, 0.01, 0.05, 1)
stars <- sapply(3:0, function(x) paste0(rep("*", x), collapse=""))

make_tbl <- function(model) {
  coefs <- summary(model)$coefficients
  coef_col <- round(coefs[,1], 2)
  se_col <- round(coefs[,2], 2)
  star_col <- stars[findInterval(coefs[,4], p_val)]
  tbl <- data.frame(coef=coef_col)
  tbl$se <- sprintf("(%0.2f)%s", se_col, star_col)
  tbl
}

make_addtorow <- function(row.name, terms) {
  # xtable allows the addition of custom rows. This function
  # makes a row with a one column (which is used for the row
  # names for the model statistics), 
  # followed by two columns that each span two columns.
  paste0(row.name, 
  paste0('& \\multicolumn{2}{C{3cm}}{', 
         terms, 
         '}', 
        collapse=''), 
  '\\\\')
}

tbl1 <- make_tbl(m1)
tbl2 <- make_tbl(m2)
combo <- merge(tbl1, tbl2, by = "row.names", all = TRUE)[,-1]
rownames(combo) <- c("Intercept", "AM: 1", "Cyl: 6", "Cyl: 8", "Horsepower", "Weight")
sum_stats <- round(rbind(glance(m1), glance(m2)), 2)

addtorow <- list()
addtorow$pos <- list(0, 6, 6, 6, 6, 6)
addtorow$command <- c(
  make_addtorow("", c("Base model", "Add Horsepower and AM")),
  make_addtorow("\\hline AIC", sum_stats$AIC), # Draw a line after coefficients
  make_addtorow("BIC", sum_stats$BIC),
  make_addtorow("Log Likelihood", sum_stats$logLik),
  make_addtorow("Deviance", sum_stats$deviance),
  make_addtorow("Num. obs.", sum_stats$df.null + 1)
  )

xtbl <- xtable(combo, add.to.row = addtorow, include.colnames = FALSE,  
               comment = FALSE)
# Specify column alignment for tabularx environment
# We're using the custom column types we created in header.tex
# \hskip specifies the width between columns
align(xtbl) <- c("L{2.5cm}", "R{1.5cm}@{\\hskip 0.1cm}", "L{1.5cm}", 
                           "R{1.5cm}@{\\hskip 0.1cm}","L{1.5cm}")

print(xtbl, 
      tabular.environment = "tabularx", # tabularx takes two arguments
      width = ".60\\textwidth",         # width, and alignment (specified above)
      add.to.row = addtorow, 
      include.colnames = FALSE,
      comment = FALSE)
```

在此处输入图像描述

于 2016-08-16T15:13:19.610 回答
1

这是使用broom. 不过，您仍然需要清理标签。

library(broom)
library(dplyr)
library(pander)
library(tidyr)

m1 = glm(mpg ~ wt + factor(cyl), data=mtcars)
m2 = glm(mpg ~ wt + factor(cyl) + hp + factor(am), data=mtcars)
base <- tidy(m1) %>% select(term, estimate) %>% mutate(type = "base_model")
with_am_hp <- tidy(m2) %>% select(term, estimate) %>% mutate(type = "Add_Horsepower_and_AM")
models <- bind_rows(base, with_am_hp)
formatted_models <- models  %>% spread(type, estimate)

m1_glance <- glance(m1) %>% mutate(type = "base_model")
m2_glance <- glance(m2) %>% mutate(type = "Add_Horsepower_and_AM")
glance_table <- data.frame("Add_Horsepower_and_AM" = unlist(glance(m2)), "base_model" = unlist(glance(m1))) %>% mutate(term = row.names(.))

full_results <- bind_rows(formatted_models, glance_table)
pandoc.table(full_results, justify = "left")
于 2016-08-16T00:12:53.900 回答