英文:
Generate summary statistics by subgroup with stargazer
问题
我尝试使用R中的stargazer生成Latex的摘要统计表。表格应该按三个子组（卢旺达/洪都拉斯/尼泊尔）对摘要统计进行排序。
当我仅为子组生成单独的表格时，它运行正常。我认为可能是国家变量引起的问题。
all_summary数据框的结构如下：
structure(list(country = structure(c("Honduras", "Nepal", "Rwanda"), label = "Country", format.stata = "%8s"), headGender = structure(c(0, 1, 0), label = "head_gender", format.stata = "%9.0g"), femaleEduc = structure(c(1, 2, 2), label = "female_educ", format.stata = "%9.0g"), maleEduc = structure(c(1, 1, 2), label = "male_educ", format.stata = "%9.0g"), wVispeople = structure(c(0, 1, 0), label = "w_visitpeople", format.stata = "%9.0g"), wVismarket = structure(c(0, 1, 1), label = "w_vismarket", format.stata = "%9.0g"), wLeavevill = structure(c(0, 1, 0), label = "w_leavevill", format.stata = "%9.0g"), fridge = structure(c(1, 0, 0), label = "fridge_owned_desired", format.stata = "%9.0g"), radio = structure(c(1, 1, 1), label = "radio_owned_desired", format.stata = "%9.0g"), fan = structure(c(0, 0, 0), label = "fan_owned_desired", format.stata = "%9.0g"), pc = structure(c(0, 0, 0), label = "pc_owned_desired", format.stata = "%9.0g"), tv = structure(c(1, 0, 1), label = "tv_owned_desired", format.stata = "%9.0g"), minutesSolid = structure(c(3, 2, 448), label = "stoveuseminutes_solids", format.stata = "%9.0g"), minutesClean = structure(c(0, 0, 0), label = "stoveuseminutes_clean", format.stata = "%9.0g"), stoveClean = structure(c(0, 0, 0), label = "stove_clean", format.stata = "%9.0g")), row.names = c(NA, -3L), class = c("tbl_df", "tbl", "data.frame"), label = "Written by R.")
以下是代码的样子：
all_summary <- allcountries %>%select(Country, head_gender, female_educ, male_educ, w_visitpeople, w_vismarket, w_leavevill, fridge_owned_desired, radio_owned_desired, fan_owned_desired, pc_owned_desired, tv_owned_desired, stoveuseminutes_solids, stoveuseminutes_clean, stove_clean) %>%rename(country = Country,headGender = head_gender,femaleEduc = female_educ,maleEduc = male_educ,wVispeople = w_visitpeople,wVismarket = w_vismarket,wLeavevill = w_leavevill,fridge = fridge_owned_desired,radio = radio_owned_desired,fan = fan_owned_desired,pc = pc_owned_desired,tv = tv_owned_desired,minutesSolid = stoveuseminutes_solids,minutesClean = stoveuseminutes_clean,stoveClean = stove_clean)# 按国家分组all_summary_grouped <- all_summary %>% group_by(country)sumstats_all_grouped <-all_summary_grouped %>%summarise_each(funs(n = sum(!is.na(.)),min = min(., na.rm = TRUE),max = max(., na.rm = TRUE),mean = mean(., na.rm = TRUE)))# 重塑数据sumstatsA <- sumstats_all_grouped %>%gather(stat, val) %>%separate(stat, into = c ("var", "stat"), sep = "_") %>%spread(stat, val) %>%select(var, n, min, max, mean)# 四舍五入sumstatsA = sumstatsA %>%mutate(mean = round(as.numeric(mean),2))# 生成表格stargazer(sumstatsA,summary = F,type = "text",digits = 2,header = F ,title = "Summary statistics for Honduras, Nepal and Rwanda",rownames = F,out = "Manuscript/Tables/SummaryAll_grouped.tex")
错误发生在# 重塑数据命令部分之后。
（在spread()中的错误：
! 输出的每一行必须由唯一的键组合标识。
键在171行之间共享：
- 112, 113, 114
- 91, 92, 93
- 106, 107, 108）
英文:
I try to generate a summary statistics table for latex in R with stargazer. The table should contain the summary statistics sorted by three subgroups (Rwanda/Honduras/Nepal).
It worked out fine, when I did seperate tables only for the subgroup. I thought maybe the country variable is the problem.
The all_summary data frame looks like this:
structure(list(country = structure(c("Honduras", "Nepal", "Rwanda"), label = "Country", format.stata = "%8s"), headGender = structure(c(0,1, 0), label = "head_gender", format.stata = "%9.0g"), femaleEduc = structure(c(1,2, 2), label = "female_educ", format.stata = "%9.0g"), maleEduc = structure(c(1,1, 2), label = "male_educ", format.stata = "%9.0g"), wVispeople = structure(c(0,1, 0), label = "w_visitpeople", format.stata = "%9.0g"), wVismarket = structure(c(0,1, 1), label = "w_vismarket", format.stata = "%9.0g"), wLeavevill = structure(c(0,1, 0), label = "w_leavevill", format.stata = "%9.0g"), fridge = structure(c(1,0, 0), label = "fridge_owned_desired", format.stata = "%9.0g"),radio = structure(c(1, 1, 1), label = "radio_owned_desired", format.stata = "%9.0g"),fan = structure(c(0, 0, 0), label = "fan_owned_desired", format.stata = "%9.0g"),pc = structure(c(0, 0, 0), label = "pc_owned_desired", format.stata = "%9.0g"),tv = structure(c(1, 0, 1), label = "tv_owned_desired", format.stata = "%9.0g"),minutesSolid = structure(c(3, 2, 448), label = "stoveuseminutes_solids", format.stata = "%9.0g"),minutesClean = structure(c(0, 0, 0), label = "stoveuseminutes_clean", format.stata = "%9.0g"),stoveClean = structure(c(0, 0, 0), label = "stove_clean", format.stata = "%9.0g")), row.names = c(NA,-3L), class = c("tbl_df", "tbl", "data.frame"), label = "Written by R.")
This is how the code looks like:
all_summary <- allcountries %>%select(Country, head_gender, female_educ, male_educ, w_visitpeople, w_vismarket, w_leavevill, fridge_owned_desired, radio_owned_desired, fan_owned_desired, pc_owned_desired, tv_owned_desired, stoveuseminutes_solids, stoveuseminutes_clean, stove_clean) %>%rename(country = Country,headGender = head_gender,femaleEduc = female_educ,maleEduc = male_educ,wVispeople = w_visitpeople,wVismarket = w_vismarket,wLeavevill = w_leavevill,fridge = fridge_owned_desired,radio = radio_owned_desired,fan = fan_owned_desired,pc = pc_owned_desired,tv = tv_owned_desired,minutesSolid = stoveuseminutes_solids,minutesClean = stoveuseminutes_clean,stoveClean = stove_clean)#Group by countryall_summary_grouped <- all_summary %>% group_by(country)sumstats_all_grouped <-all_summary_grouped %>%summarise_each(funs(n = sum(!is.na(.)),min = min(., na.rm = TRUE),max = max(., na.rm = TRUE),mean = mean(., na.rm = TRUE)))#Reshape datasumstatsA <- sumstats_all_grouped %>%gather(stat, val) %>%separate(stat, into = c ("var", "stat"), sep = "_") %>%spread(stat, val) %>%select(var, n, min, max, mean)#RoundsumstatsA = sumstatsA %>%mutate(mean = round(as.numeric(mean),2))#produce tablestargazer(sumstatsA,summary = F,type = "text",digits = 2,header = F ,title = "Summary statistics for Honduras, Nepal and Rwanda",rownames = F,out = "Manuscript/Tables/SummaryAll_grouped.tex")
The error happens after the #Reshape data command section
(Error in spread():
! Each row of output must be identified by a unique combination of keys.
Keys are shared for 171 rows:
- 112, 113, 114
- 91, 92, 93
- 106, 107, 108
(to be continued))
答案1
得分: 0
以下是一些最小的原始数据：
library(tidyverse)data(mtcars)as_tibble(mtcars)
这是gtsummary包，它可以生成每个组（例如，cyl）的简单摘要统计信息，默认以HTML格式呈现（您可以对表格进行各种修改）：
library(gtsummary)mtcars %>% tbl_summary(by = cyl)
有选项可以将其打印为.tex文件：
# 打印为.tex文件as_kable_extra(mtcars %>% tbl_summary(by = cyl), format = "latex")
以下是可以通过选项指定的各种统计数据，现在显示非缺失值的数量，均值，中位数，P25和P75以及从最小值到最大值的范围：
mtcars %>% tbl_summary(by = am,type = all_continuous() ~ "continuous2",statistic = all_continuous() ~ c("{N_nonmiss}","{mean}","{median} ({p25}, {p75})","{min}, {max}"))
请注意，以上是一些R代码的片段和描述，无法提供完整的交互式演示。如果您需要更多详细信息或特定翻译，请提出具体问题。
英文:
Here is some minimal raw data:
library(tidyverse)data(mtcars)as_tibble(mtcars)# A tibble: 32 × 11mpg cyl disp hp drat wt qsec vs am gear carb<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>1 21 6 160 110 3.9 2.62 16.5 0 1 4 42 21 6 160 110 3.9 2.88 17.0 0 1 4 43 22.8 4 108 93 3.85 2.32 18.6 1 1 4 14 21.4 6 258 110 3.08 3.22 19.4 1 0 3 15 18.7 8 360 175 3.15 3.44 17.0 0 0 3 26 18.1 6 225 105 2.76 3.46 20.2 1 0 3 17 14.3 8 360 245 3.21 3.57 15.8 0 0 3 48 24.4 4 147. 62 3.69 3.19 20 1 0 4 29 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 210 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4# … with 22 more rows# ℹ Use `print(n = ...)` to see more rows
This is the gtsummary package that produces easy summary statistics per group (e.g. cyl) in default html format (you can have various modifications for the table):
library(gtsummary)mtcars %>% tbl_summary(by = cyl)
There are options to print this as .tex:
# print as texas_kable_extra(mtcars %>% tbl_summary(by = cyl), format = "latex")\begin{tabular}{l|c|c|c}\hline\textbf{Characteristic} & \textbf{4}, N = 11 & \textbf{6}, N = 7 & \textbf{8}, N = 14\\\hlinempg & 26.0 (22.8, 30.4) & 19.7 (18.6, 21.0) & 15.2 (14.4, 16.2)\\\hlinedisp & 108 (79, 121) & 168 (160, 196) & 350 (302, 390)\\\hlinehp & 91 (66, 96) & 110 (110, 123) & 192 (176, 241)\\\hlinedrat & 4.08 (3.81, 4.16) & 3.90 (3.35, 3.91) & 3.12 (3.07, 3.22)\\\hlinewt & 2.20 (1.89, 2.62) & 3.21 (2.82, 3.44) & 3.76 (3.53, 4.01)\\\hlineqsec & 18.90 (18.56, 19.95) & 18.30 (16.74, 19.17) & 17.18 (16.10, 17.56)\\\hlinevs & 10 (91\%) & 4 (57\%) & 0 (0\%)\\\hlineam & 8 (73\%) & 3 (43\%) & 2 (14\%)\\\hlinegear & & & \\\hline\hspace{1em}3 & 1 (9.1\%) & 2 (29\%) & 12 (86\%)\\\hline\hspace{1em}4 & 8 (73\%) & 4 (57\%) & 0 (0\%)\\\hline\hspace{1em}5 & 2 (18\%) & 1 (14\%) & 2 (14\%)\\\hlinecarb & & & \\\hline\hspace{1em}1 & 5 (45\%) & 2 (29\%) & 0 (0\%)\\\hline\hspace{1em}2 & 6 (55\%) & 0 (0\%) & 4 (29\%)\\\hline\hspace{1em}3 & 0 (0\%) & 0 (0\%) & 3 (21\%)\\\hline\hspace{1em}4 & 0 (0\%) & 4 (57\%) & 6 (43\%)\\\hline\hspace{1em}6 & 0 (0\%) & 1 (14\%) & 0 (0\%)\\\hline\hspace{1em}8 & 0 (0\%) & 0 (0\%) & 1 (7.1\%)\\\hline\multicolumn{4}{l}{\rule{0pt}{1em}\textsuperscript{1} Median (IQR); n (\%)}\\\end{tabular}
Update
Here is a list of various statistics that you can specify via options. It now shows the number of non-missings, the mean, the median, p25 and p75 and the range from min to max.
mtcars %>% tbl_summary(by = am,type = all_continuous() ~ "continuous2",statistic = all_continuous() ~ c("{N_nonmiss}","{mean}","{median} ({p25}, {p75})","{min}, {max}"))
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