stargazer 学习笔记

李家翔

2019-06-24

1. 使用 RMarkdown 的 child 参数，进行文档拼接。
2. 这样拼接以后的笔记方便复习。
3. 相关问题提交到 GitHub

1 介绍

You can use the style argument to choose a template of your choice. Economics and management scholars can thus create tables that resemble those published in the American Economic Review, in the Quarterly Journal of Economics, or in Administrative Science Quarterly. Political scientists can avail themselves of templates based on the American Political Science Review, the American Journal of Political Science, and on International Organization. For sociologists and demographers, the American Sociological Review, the American Sociological Reviews and Demography are available. www.r-bloggers.com

stargazer (占星师) 是一个广泛用于发表的制表软件包。

参考 Torres-Reyna (2014) stargazer 主要美化两方面

1. 描述性统计展示
2. 模型展示

并且导出到 Word 文档，方便整合。

2 描述性统计展示

library(stargazer)
desc_path <- "../output/desc.doc"
stargazer(mtcars, type = "html", out = desc_path)

Statistic	N	Mean	St. Dev.	Min	Pctl(25)	Pctl(75)	Max
mpg	32	20.091	6.027	10	15.4	22.8	34
cyl	32	6.188	1.786	4	4	8	8
disp	32	230.722	123.939	71	120.8	326	472
hp	32	146.688	68.563	52	96.5	180	335
drat	32	3.597	0.535	2.760	3.080	3.920	4.930
wt	32	3.217	0.978	1.513	2.581	3.610	5.424
qsec	32	17.849	1.787	14.500	16.892	18.900	22.900
vs	32	0.438	0.504	0	0	1	1
am	32	0.406	0.499	0	0	1	1
gear	32	3.688	0.738	3	3	4	5
carb	32	2.812	1.615	1	2	4	8

见展示 Word 文档

Output as html, which produce editable tables for Word documents. (Torres-Reyna 2014)

type = "html"限定导出的 word 文档中表格已经 latex 化。

library(tidyverse)
mtcars %>% 
    gather() %>% 
    group_by(key) %>% 
    summarise(mean = mean(value), sd = sd(value)) %>% 
    stargazer(type = "html", out = desc_path, summary = FALSE)

	key	mean	sd
1	am	0.40625	0.498990917235846
2	carb	2.8125	1.61519997763185
3	cyl	6.1875	1.78592164694654
4	disp	230.721875	123.938693831382
5	drat	3.5965625	0.534678736070971
6	gear	3.6875	0.737804065256947
7	hp	146.6875	68.5628684893206
8	mpg	20.090625	6.0269480520891
9	qsec	17.84875	1.78694323609684
10	vs	0.4375	0.504016128774185
11	wt	3.21725	0.978457442989697

# 自定义描述性统计

见展示 Word 文档

library(stargazer)
stargazer(mtcars, type = "html",  title="Descriptive statistics", digits=3, out = desc_path)

Descriptive statistics

Statistic	N	Mean	St. Dev.	Min	Pctl(25)	Pctl(75)	Max
mpg	32	20.091	6.027	10	15.4	22.8	34
cyl	32	6.188	1.786	4	4	8	8
disp	32	230.722	123.939	71	120.8	326	472
hp	32	146.688	68.563	52	96.5	180	335
drat	32	3.597	0.535	2.760	3.080	3.920	4.930
wt	32	3.217	0.978	1.513	2.581	3.610	5.424
qsec	32	17.849	1.787	14.500	16.892	18.900	22.900
vs	32	0.438	0.504	0	0	1	1
am	32	0.406	0.499	0	0	1	1
gear	32	3.688	0.738	3	3	4	5
carb	32	2.812	1.615	1	2	4	8

见展示 Word 文档

title="Descriptive statistics", digits=3 加入标题和有效数字限制(论文使用3)。

library(stargazer)
stargazer(mtcars, type = "html",  title="Descriptive statistics", digits=3, out = desc_path,
          
covariate.labels=c("Miles/(US)gallon","No. of cylinders","Displacement (cu.in.)",
 "Gross horsepower","Rear axle ratio","Weight (lb/1000)",
 "1/4 mile time","V/S","Transmission (0=auto, 1=manual)",
 "Number of forward gears","Number of carburetors")
          )

Descriptive statistics

Statistic	N	Mean	St. Dev.	Min	Pctl(25)	Pctl(75)	Max
Miles/(US)gallon	32	20.091	6.027	10	15.4	22.8	34
No. of cylinders	32	6.188	1.786	4	4	8	8
Displacement (cu.in.)	32	230.722	123.939	71	120.8	326	472
Gross horsepower	32	146.688	68.563	52	96.5	180	335
Rear axle ratio	32	3.597	0.535	2.760	3.080	3.920	4.930
Weight (lb/1000)	32	3.217	0.978	1.513	2.581	3.610	5.424
1/4 mile time	32	17.849	1.787	14.500	16.892	18.900	22.900
V/S	32	0.438	0.504	0	0	1	1
Transmission (0=auto, 1=manual)	32	0.406	0.499	0	0	1	1
Number of forward gears	32	3.688	0.738	3	3	4	5
Number of carburetors	32	2.812	1.615	1	2	4	8

covariate.labels 加入变量名称（非字母），这样让描述性统计更加直观。

Use the option covariate.labels to replace variable names with variable labels. Must be in same order as in the dataset.

注意变量数和 label 数要保持一致。

3 模型展示

library(stargazer)
models_path <- "../output/models.doc"
mtcars$fast <-
    as.numeric((mtcars$mpg > 20.1)) #Creating a dummy variable 1 = fast car
m1 <- lm(mpg ~ hp, data = mtcars)
m2 <- lm(mpg ~ hp + drat, data = mtcars)
m3 <- lm(mpg ~ hp + drat + factor(gear), data = mtcars)
m4 <-
    glm(fast ~ hp + drat + am,
        family = binomial(link = "logit"),
        data = mtcars)
stargazer(
    m1,
    m2,
    m3,
    m4,
    type = "html",
    dep.var.labels = c("Miles/(US) gallon", "Fast car (=1)"),
    covariate.labels = c(
        "Gross horsepower",
        "Rear axle ratio",
        "Four foward gears",
        "Five forward gears",
        "Type of transmission (manual=1)"
    ),
    out = models_path
)

	Dependent variable:
	Miles/(US) gallon			Fast car (=1)
	OLS			logistic
	(1)	(2)	(3)	(4)
Gross horsepower	-0.068***	-0.052***	-0.064***	-0.397
	(0.010)	(0.009)	(0.011)	(1.358)
Rear axle ratio		4.698***	3.510*	4.248
		(1.192)	(1.851)	(21.106)
Four foward gears			-0.276
			(2.135)
Five forward gears			3.761*
			(2.161)
Type of transmission (manual=1)				11.743
				(359.486)
Constant	30.099***	10.790**	16.306**	29.882
	(1.634)	(5.078)	(6.429)	(85.238)
Observations	32	32	32	32
R2	0.602	0.741	0.782
Adjusted R2	0.589	0.723	0.749
Log Likelihood				-1.953
Akaike Inf. Crit.				11.906
Residual Std. Error	3.863 (df = 30)	3.170 (df = 29)	3.017 (df = 27)
F Statistic	45.460*** (df = 1; 30)	41.522*** (df = 2; 29)	24.179*** (df = 4; 27)
Note:	p<0.1; p<0.05; p<0.01

设定好 dep.var.labels 因变量名称（非字母），covariate.labels

参考文献

Torres-Reyna, Oscar. 2014. “Using Stargazer to Report Regression Output and Descriptive Statistics in R: For Non-Latex Users.” Princeton University DSS Lab. 2014. https://www.princeton.edu/~otorres/NiceOutputR.pdf.