使用Stargazer包按分类变量获取单独的摘要统计信息
Mic*_*ael 8 r summary stargazer
我想使用stargazer为分组变量的每个类别生成摘要统计信息.我可以在单独的表中完成它,但我喜欢它在一个 - 如果这对于这个包没有不合理的挑战.
例如
library(stargazer)
stargazer(ToothGrowth, type = "text")
#>
#> =========================================
#> Statistic N Mean St. Dev. Min Max
#> -----------------------------------------
#> len 60 18.813 7.649 4.200 33.900
#> dose 60 1.167 0.629 0.500 2.000
#> -----------------------------------------
提供了连续变量的夏季统计数据ToothGrowth.我想用分类变量将该夏季分开supp,也在ToothGrowth.
对期望结果的两点建议,
stargazer(ToothGrowth ~ supp, type = "text")
#>
#> ==================================================
#> Statistic N Mean St. Dev. Min Max
#> --------------------------------------------------
#> OJ len 30 16.963 8.266 4.200 33.900
#> dose 30 1.167 0.634 0.500 2.000
#> VC len 30 20.663 6.606 8.200 30.900
#> dose 30 1.167 0.634 0.500 2.000
#> --------------------------------------------------
#>
stargazer(ToothGrowth ~ supp, type = "text")
#>
#> ==================================================
#> Statistic N Mean St. Dev. Min Max
#> --------------------------------------------------
#> len
#> _by VC 30 16.963 8.266 4.200 33.900
#> _by VC 30 1.167 0.634 0.500 2.000
#> _tot 60 18.813 7.649 4.200 33.900
#>
#> dose
#> _by OJ 30 20.663 6.606 8.200 30.900
#> _by OJ 30 1.167 0.634 0.500 2.000
#> _tot 60 1.167 0.629 0.500 2.000
#> --------------------------------------------------
解
library(stargazer)
library(dplyr)
library(tidyr)
ToothGrowth %>%
group_by(supp) %>%
mutate(id = 1:n()) %>%
ungroup() %>%
gather(temp, val, len, dose) %>%
unite(temp1, supp, temp, sep = '_') %>%
spread(temp1, val) %>%
select(-id) %>%
as.data.frame() %>%
stargazer(type = 'text')
结果
=========================================
Statistic N Mean St. Dev. Min Max
-----------------------------------------
OJ_dose 30 1.167 0.634 0.500 2.000
OJ_len 30 20.663 6.606 8.200 30.900
VC_dose 30 1.167 0.634 0.500 2.000
VC_len 30 16.963 8.266 4.200 33.900
-----------------------------------------
说明
这解决了OP在对原始答案的评论中提到的问题,"我真正想要的是一个表格,其中汇总统计信息由分类变量分隔,而不是创建单独的表格." 我看到这样做与最简单的方法stargazer是创建一个使用过的每个组的观察变量,新的数据帧gather(),unite(),spread()策略.唯一的技巧是通过按组创建唯一标识符并在调用之前删除该变量来避免重复标识符stargazer().
三种可能的解决方案。一种使用reporttools和xtable，一种使用tidyverse工具和stargazer，第三种是base-r解决方案。
第一的，
我想建议你看看reporttools，它有点离开 stargazer，但我认为你应该看看它，
# install.packages("reporttools") #Use this to install it, do this only once
require(reporttools)
vars <- ToothGrowth[,c('len','dose')]
group <- ToothGrowth[,c('supp')]
## display default statistics, only use a subset of observations, grouped analysis
tableContinuous(vars = vars, group = group, prec = 1, cap = "Table of 'len','dose' by 'supp' ", lab = "tab: descr stat")
% latex table generated in R 3.3.3 by xtable 1.8-2 package
\begingroup\footnotesize
\begin{longtable}{llrrrrrrrrrr}
\textbf{Variable} & \textbf{Levels} & $\mathbf{n}$ & \textbf{Min} & $\mathbf{q_1}$ & $\mathbf{\widetilde{x}}$ & $\mathbf{\bar{x}}$ & $\mathbf{q_3}$ & \textbf{Max} & $\mathbf{s}$ & \textbf{IQR} & \textbf{\#NA} \\
\hline
len & OJ & 30 & 8.2 & 15.5 & 22.7 & 20.7 & 25.7 & 30.9 & 6.6 & 10.2 & 0 \\
& VC & 30 & 4.2 & 11.2 & 16.5 & 17.0 & 23.1 & 33.9 & 8.3 & 11.9 & 0 \\
\hline
& all & 60 & 4.2 & 13.1 & 19.2 & 18.8 & 25.3 & 33.9 & 7.6 & 12.2 & 0 \\
\hline
dose & OJ & 30 & 0.5 & 0.5 & 1.0 & 1.2 & 2.0 & 2.0 & 0.6 & 1.5 & 0 \\
& VC & 30 & 0.5 & 0.5 & 1.0 & 1.2 & 2.0 & 2.0 & 0.6 & 1.5 & 0 \\
\hline
& all & 60 & 0.5 & 0.5 & 1.0 & 1.2 & 2.0 & 2.0 & 0.6 & 1.5 & 0 \\
\hline
\hline
\caption{Table of 'len','dose' by 'supp' }
\label{tab: descr stat}
\end{longtable}
\endgroup
在乳胶中你会得到这个很好的结果，
第二，
使用tidyverse工具和stargazer，受到这个 SO 答案的启发，
# install.packages(c("tidyverse"), dependencies = TRUE)
library(dplyr); library(purrr)
#> ToothGrowth %>% split(. $supp) %>% walk(~ stargazer(., type = "text"))
#> =========================================
#> Statistic N Mean St. Dev. Min Max
#> -----------------------------------------
#> len 30 20.663 6.606 8.200 30.900
#> dose 30 1.167 0.634 0.500 2.000
#> -----------------------------------------
#> =========================================
#> Statistic N Mean St. Dev. Min Max
#> -----------------------------------------
#> len 30 16.963 8.266 4.200 33.900
#> dose 30 1.167 0.634 0.500 2.000
#> -----------------------------------------
#>
第三，
独家的base-r
by(ToothGrowth, ToothGrowth$supp, stargazer, type = 'text')
#> =========================================
#> Statistic N Mean St. Dev. Min Max
#> -----------------------------------------
#> len 30 20.663 6.606 8.200 30.900
#> dose 30 1.167 0.634 0.500 2.000
#> -----------------------------------------
#>
#> =========================================
#> Statistic N Mean St. Dev. Min Max
#> -----------------------------------------
#> len 30 16.963 8.266 4.200 33.900
#> dose 30 1.167 0.634 0.500 2.000
#> -----------------------------------------
#> ToothGrowth$supp: OJ
#> [1] ""
#> [2] "========================================="
#> [3] "Statistic N Mean St. Dev. Min Max "
#> [4] "-----------------------------------------"
#> [5] "len 30 20.663 6.606 8.200 30.900"
#> [6] "dose 30 1.167 0.634 0.500 2.000 "
#> [7] "-----------------------------------------"
#> ---------------------------------------------------------------
#> ToothGrowth$supp: VC
#> [1] ""
#> [2] "========================================="
#> [3] "Statistic N Mean St. Dev. Min Max "
#> [4] "-----------------------------------------"
#> [5] "len 30 16.963 8.266 4.200 33.900"
#> [6] "dose 30 1.167 0.634 0.500 2.000 "
#> [7] "-----------------------------------------"