我的目标是建立一个回归表，其中的列按小数点分隔符对齐。
我生成了一个回归输出（使用 Stata）并使用用户编写的包将其导出esttab。在 LaTeX 中，我使用该包siunitx及其S列进行对齐。
但是，输出结果看起来很糟糕，表格没有正确处理括号中的不确定值（标准误差），系数和标准误差之间的差距太大。结果，一列中的标准误差覆盖了下一列中的系数。
有人知道如何从中得到一个美观的（和一致的）输出吗（理想情况下，不会引入太多额外的包或特殊的修复，因为这些会阻碍通过例程实现自动化esttab）？我试过separate-uncertainty，uncertainty-separator和其他选项，但都无济于事。
% Key code in Latex
\usepackage{siunitx}
\sisetup{
input-signs = -,
input-symbols = Yes,
input-open-uncertainty = ,
input-close-uncertainty = ,
round-mode = places,
round-precision = 2,
}
\begin{table}[!h]
\centering
\caption{XXX}
\label{tab:4}
\begin{adjustbox}{max width=6in}
\input{Table_4.tex}
\end{adjustbox}
\\[3pt]
\begin{minipage}{6in}
\footnotesize{Note: Significance levels: $^{+}\ p<0.1, ^{*}\ p<0.05$, ^{**}\ p<0.01$, ^{***}\ p<0.001.$}
\end{minipage}
\end{table} \\
% Table output
{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l S[table-format = 1.2(3),table-figures-uncertainty=1] S[table-format = 1.2(3),table-figures-uncertainty=1]
S[table-format = 1.2(3),table-figures-uncertainty=1]}
\hline\hline
&\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
&\multicolumn{1}{c}{\shortstack{\\IEF}}&\multicolumn{1}{c}{\shortstack{\\Contact}}&\multicolumn{1}{c}{\shortstack{\\Interaction}}\\
\hline
SUV &-0.38(0.09)\sym{***}&-0.49 (0.14)\sym{***}&-0.46 (0.19)\sym{*} \\
SUV X Yes & & &-0.33 (0.16)\sym{*} \\
Yes & & 0.30 (0.08)\sym{***}& 0.55 (0.13)\sym{***}\\
SUV X NO & & & 0.02 (0.26) \\
NO & &-0.21 (0.24) &-0.21 (0.36) \\
Age & 0.09 (0.01)\sym{***}& 0.09 (0.01)\sym{***}& 0.09 (0.01)\sym{***}\\
Age² &-0.00 (0.00)\sym{***}&-0.00 (0.00)\sym{***}&-0.00 (0.00)\sym{***}\\
Female & 0.01 (0.03) & 0.01 (0.03) & 0.01 (0.03) \\
Education: Primary & 0.31 (0.11)\sym{**} & 0.30 (0.11)\sym{**} & 0.30 (0.11)\sym{**} \\
Education: Secondary & 0.62 (0.12)\sym{***}& 0.61 (0.12)\sym{***}& 0.61 (0.12)\sym{***}\\
Education: Post-Secondary& 0.67 (0.11)\sym{***}& 0.67 (0.11)\sym{***}& 0.67 (0.11)\sym{***}\\
Education: University & 1.13 (0.14)\sym{***}& 1.12 (0.14)\sym{***}& 1.12 (0.14)\sym{***}\\
Income: Quintile 2 & 0.16 (0.07)\sym{*} & 0.16 (0.07)\sym{*} & 0.16 (0.07)\sym{*} \\
Income: Quintile 3 & 0.30 (0.06)\sym{***}& 0.30 (0.06)\sym{***}& 0.30 (0.06)\sym{***}\\
Income: Quintile 4 & 0.51 (0.05)\sym{***}& 0.51 (0.05)\sym{***}& 0.51 (0.05)\sym{***}\\
Income: Quintile 5 & 0.52 (0.10)\sym{***}& 0.52 (0.10)\sym{***}& 0.52 (0.10)\sym{***}\\
Small/Mid-Sized Town &-0.10 (0.06)\sym{+} &-0.10 (0.06)\sym{+} &-0.10 (0.06)\sym{+} \\
Suburb of a Large City &-0.11 (0.06)\sym{+} &-0.11 (0.06)\sym{+} &-0.11 (0.06)\sym{+} \\
Large City &-0.11 (0.08) &-0.11 (0.08) &-0.11 (0.08) \\
Close to a Party & 0.98 (0.05)\sym{***}& 0.97 (0.05)\sym{***}& 0.97 (0.05)\sym{***}\\
Efficacy & 0.34 (0.02)\sym{***}& 0.34 (0.02)\sym{***}& 0.34 (0.02)\sym{***}\\
Constant &-4.05 (0.25)\sym{***}&-3.98 (0.23)\sym{***}&-4.01 (0.27)\sym{***}\\\hline
Country-Year Variance & 0.04 (0.01)\sym{***}& 0.06 (0.03)\sym{+} & 0.06 (0.03)\sym{+} \\
\hline
Country FE &\multicolumn{1}{c}{Yes} &\multicolumn{1}{c}{Yes} &\multicolumn{1}{c}{Yes} \\
N (individuals) &\multicolumn{1}{c}{75183} &\multicolumn{1}{c}{75183} &\multicolumn{1}{c}{75183} \\
N (elections) &\multicolumn{1}{c}{64} &\multicolumn{1}{c}{64} &\multicolumn{1}{c}{64} \\
\hline\hline
\multicolumn{4}{l}{\footnotesize }\\
\end{tabular}
}
LaTeX 输出：
答案1
您可能没有意识到，自然科学中以表格形式显示“不确定性”度量的方式与回归结果的统计报告方式截然不同。siunitx默认情况下，它适合自然科学的做事方式。但在回归表中，标准误差通常显示在单独的行中，以下相应的系数。
无论如何，我建议您将标准错误放在单独的行上。
另一条评论：由于所有数字似乎都已四舍五入到小数点后两位，因此选项round-mode = places和round-precision = 2似乎不需要。
\documentclass{article}
\usepackage{siunitx}
\sisetup{input-open-uncertainty = ,
input-close-uncertainty = ,
table-space-text-pre = (,
table-space-text-post = \sym{***},
table-align-text-pre = false,
table-align-text-post = false}
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\usepackage{booktabs}
\begin{document}
\begin{table}[!h]
\centering
\caption{XXX\strut}
\label{tab:4}
\begin{tabular}{@{} l *{3}{S[table-format = -1.2]} @{}}
\toprule
& {(1)} & {(2)} & {(3)} \\
& {IEF} & {Contact} & {Interaction}\\
\midrule
SUV &-0.38\sym{***}&-0.49 \sym{***}&-0.46 \sym{*} \\
& (0.09) & (0.14) & (0.19) \\
SUV$\times$Yes & & &-0.33\sym{*} \\
& & & (0.16) \\
Yes & & 0.30 \sym{***}& 0.55 \sym{***}\\
& & (0.08) & (0.13) \\
$\vdots$ \\
\midrule
Country FE & {Yes} & {Yes} & {Yes} \\
$N$ (individuals) & {75183} & {75183} & {75183} \\
$N$ (elections) & {64} & {64} & {64} \\
\bottomrule
\end{tabular}
\medskip\footnotesize
Note: Significance levels: $^{+}\ p<0.1$, $^{*}\ p<0.05$, $^{**}\ p<0.01$, $^{***}\ p<0.001$.
\end{table}
\end{document}
答案2
以下是我的建议：
\documentclass{article}
\usepackage{siunitx}
\usepackage{booktabs}
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{document}
\begin{table}[!h]
\centering
\caption{XXX}
\label{tab:4}
\sisetup{table-space-text-post=\sym{***},
table-align-text-post=false,
table-format = -1.2(3)}
\setlength{\tabcolsep}{0pt}
\begin{tabular*}{\textwidth}{@{\extracolsep{\fill}}lSSS}
\toprule
& {(1)} & {(2)} & {(3)} \\
& {IEF} & {Contact} & {Interaction} \\
\hline
SUV & -0.38 (9)\sym{***} & -0.49 (14)\sym{***} & -0.46 (19)\sym{*} \\
SUV X Yes & & & -0.33 (16)\sym{*} \\
Yes & & 0.30 (8)\sym{***} & 0.55 (13)\sym{***} \\
SUV X NO & & & 0.02 (26) \\
NO & & -0.21 (24) & -0.21 (36) \\
Age & 0.09 (1)\sym{***} & 0.09 (1)\sym{***} & 0.09 (1)\sym{***} \\
Age² & -0.00 (0)\sym{***} & -0.00 (0)\sym{***} & -0.00 (0)\sym{***} \\
Female & 0.01 (3) & 0.01 (3) & 0.01 (3) \\
Education: Primary & 0.31 (11)\sym{**} & 0.30 (11)\sym{**} & 0.30 (11)\sym{**} \\
Education: Secondary & 0.62 (12)\sym{***} & 0.61 (12)\sym{***} & 0.61 (12)\sym{***} \\
Education: Post-Secondary & 0.67 (11)\sym{***} & 0.67 (11)\sym{***} & 0.67 (11)\sym{***} \\
Education: University & 1.13 (14)\sym{***} & 1.12 (14)\sym{***} & 1.12 (14)\sym{***} \\
Income: Quintile 2 & 0.16 (7)\sym{*} & 0.16 (7)\sym{*} & 0.16 (7)\sym{*} \\
Income: Quintile 3 & 0.30 (6)\sym{***} & 0.30 (6)\sym{***} & 0.30 (6)\sym{***} \\
Income: Quintile 4 & 0.51 (5)\sym{***} & 0.51 (5)\sym{***} & 0.51 (5)\sym{***} \\
Income: Quintile 5 & 0.52 (10)\sym{***} & 0.52 (10)\sym{***} & 0.52 (10)\sym{***} \\
Small/Mid-Sized Town & -0.10 (6)\sym{+} & -0.10 (6)\sym{+} & -0.10 (6)\sym{+} \\
Suburb of a Large City & -0.11 (6)\sym{+} & -0.11 (6)\sym{+} & -0.11 (6)\sym{+} \\
Large City & -0.11 (8) & -0.11 (8) & -0.11 (8) \\
Close to a Party & 0.98 (5)\sym{***} & 0.97 (5)\sym{***} & 0.97 (5)\sym{***} \\
Efficacy & 0.34 (2)\sym{***} & 0.34 (2)\sym{***} & 0.34 (2)\sym{***} \\
Constant & -4.05 (25)\sym{***} & -3.98 (23)\sym{***} & -4.01 (27)\sym{***} \\
\midrule
Country-Year Variance & 0.04 (1)\sym{***} & 0.06 (3)\sym{+} & 0.06 (3)\sym{+} \\
\midrule
Country FE & {Yes} & {Yes} & {Yes} \\
N (individuals) & {75183} & {75183} & {75183} \\
N (elections) & {64} & {64} & {64} \\
\bottomrule
\multicolumn{4}{l}{\footnotesize Note: Significance levels: \sym{+} p<0.1, \sym{*} p<0.05, \sym{**} p<0.01, \sym{***} p<0.001.}
\end{tabular*}
\end{table}
\end{document}
答案3
再次感谢您的有益建议。
最后，我发现了另一种方法来获得我想要的东西dcolumn。为了使其正常工作，我必须在回归输出中的回归系数和标准误差之间添加小空格（子句incelldelimite("\:")）esttab。
% Code
\documentclass[letterpaper,12pt]{article}
\usepackage[utf8]{inputenc}
\usepackage{adjustbox}
\usepackage{booktabs,subcaption,amsfonts,dcolumn}
\newcolumntype{d}[1]{D..{#1}}
\begin{document}
\begin{table}[!h]
\centering
\caption{xxxx}
\label{tab:4}
\begin{adjustbox}{max width=6in}
\input{Table_4.tex}
\end{adjustbox}
\\[3pt]
\begin{minipage}{6in}
\footnotesize{Note: Hierarchical logistic regression with country fixed effects and random intercepts by election. Standard errors in parentheses. Significance levels: $^{+}\ p<0.1, ^{*}\ p<0.05$, ^{**}\ p<0.01$, ^{***}\ p<0.001.$}
\end{minipage}
\end{table} \\
% Table
{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{3}{d{10}}}
\hline\hline
&\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
&\multicolumn{1}{c}{\shortstack{\\SUV}}&\multicolumn{1}{c}{\shortstack{\\Yes}}&\multicolumn{1}{c}{\shortstack{\\Interaction}}\\
\hline
SUV &-0.38\:(0.09)\sym{***}&-0.49\:(0.14)\sym{***}&-0.46\:(0.19)\sym{*} \\
SUV X Contact: Yes & \: & \: &-0.33\:(0.16)\sym{*} \\
Yes & \: &0.30\:(0.08)\sym{***}&0.55\:(0.13)\sym{***}\\
SUV X Contact: No & \: & \: &0.02\:(0.26) \\
No & \: &-0.21\:(0.24) &-0.21\:(0.36) \\
Age &0.09\:(0.01)\sym{***}&0.09\:(0.01)\sym{***}&0.09\:(0.01)\sym{***}\\
Age^2 &-0.00\:(0.00)\sym{***}&-0.00\:(0.00)\sym{***}&-0.00\:(0.00)\sym{***}\\
Female &0.01\:(0.03) &0.01\:(0.03) &0.01\:(0.03) \\
Education: Primary &0.31\:(0.11)\sym{**} &0.30\:(0.11)\sym{**} &0.30\:(0.11)\sym{**} \\
Education: Secondary &0.62\:(0.12)\sym{***}&0.61\:(0.12)\sym{***}&0.61\:(0.12)\sym{***}\\
Education: Post-Secondary&0.67\:(0.11)\sym{***}&0.67\:(0.11)\sym{***}&0.67\:(0.11)\sym{***}\\
Education: University &1.13\:(0.14)\sym{***}&1.12\:(0.14)\sym{***}&1.12\:(0.14)\sym{***}\\
Income: Quintile 2 &0.16\:(0.07)\sym{*} &0.16\:(0.07)\sym{*} &0.16\:(0.07)\sym{*} \\
Income: Quintile 3 &0.30\:(0.06)\sym{***}&0.30\:(0.06)\sym{***}&0.30\:(0.06)\sym{***}\\
Income: Quintile 4 &0.51\:(0.05)\sym{***}&0.51\:(0.05)\sym{***}&0.51\:(0.05)\sym{***}\\
Income: Quintile 5 &0.52\:(0.10)\sym{***}&0.52\:(0.10)\sym{***}&0.52\:(0.10)\sym{***}\\
Small/Mid-Sized Town &-0.10\:(0.06)\sym{+} &-0.10\:(0.06)\sym{+} &-0.10\:(0.06)\sym{+} \\
Suburb of a Large City &-0.11\:(0.06)\sym{+} &-0.11\:(0.06)\sym{+} &-0.11\:(0.06)\sym{+} \\
Large City &-0.11\:(0.08) &-0.11\:(0.08) &-0.11\:(0.08) \\
Close to a Party &0.98\:(0.05)\sym{***}&0.97\:(0.05)\sym{***}&0.97\:(0.05)\sym{***}\\
Efficacy &0.34\:(0.02)\sym{***}&0.34\:(0.02)\sym{***}&0.34\:(0.02)\sym{***}\\
Constant &-4.05\:(0.25)\sym{***}&-3.98\:(0.23)\sym{***}&-4.01\:(0.27)\sym{***}\\\hline
Country-Year Variance &0.04\:(0.01)\sym{***}&0.06\:(0.03)\sym{+} &0.06\:(0.03)\sym{+} \\
\hline
Country FE &\multicolumn{1}{c}{Yes} &\multicolumn{1}{c}{Yes} &\multicolumn{1}{c}{Yes} \\
N (individuals) &\multicolumn{1}{c}{75183} &\multicolumn{1}{c}{75183} &\multicolumn{1}{c}{75183} \\
N (elections) &\multicolumn{1}{c}{64} &\multicolumn{1}{c}{64} &\multicolumn{1}{c}{64} \\
\hline\hline
\multicolumn{4}{l}{\footnotesize }\\
\end{tabular}
}
