我想从同一行中的几个回归中输出交互项,并将其称为“#34;交互”#34;。到目前为止,我所拥有的是交互术语出现在两个不同的行中,称为" Interaction" (见下面的代码)。
此问题已在此处提出,但我的分数还不够高,尚未对其进行评论或评论:https://stackoverflow.com/questions/28859569/several-coefficients-in-one-line。
library("stargazer")
stargazer(attitude)
stargazer(attitude, summary=FALSE)
# 2 OLS models with Interactions
linear.1 <- lm(rating ~ complaints + privileges + complaints*privileges
, data=attitude)
linear.2 <- lm(rating ~ complaints + learning + complaints*learning, data=attitude)
stargazer(linear.1, linear.2, title="Regression Results", type="text",
covariate.labels=c("Complaints", "Privileges", "Interaction", "Learning", "Interaction"))
感谢您的帮助。
答案 0 :(得分:2)
我认为这不是本机支持的,因为它不是一个好主意。您要求对表格中数字的含义进行模糊处理,这无法帮助您的读者。
现在说明了这一点,你可以通过修改lm
个对象的内容来实现这个目的:
# copy objects just for demonstration
m1 <- linear.1
m2 <- linear.2
# see names of coefficients
names(m1$coefficients)
# [1] "(Intercept)" "complaints" "privileges" "complaints:privileges"
names(m2$coefficients)
# [1] "(Intercept)" "complaints" "learning" "complaints:learning"
# replace names
names(m1$coefficients)[names(m1$coefficients) == "complaints:privileges"] <- "interaction"
names(m2$coefficients)[names(m2$coefficients) == "complaints:learning"] <- "interaction"
结果:
> stargazer(m1, m2, title="Regression Results", type="text")
Regression Results
==========================================================
Dependent variable:
----------------------------
rating
(1) (2)
----------------------------------------------------------
complaints 1.114** 0.307
(0.401) (0.503)
privileges 0.434
(0.570)
learning -0.171
(0.570)
interaction -0.007 0.006
(0.008) (0.009)
Constant -7.737 31.203
(27.409) (31.734)
----------------------------------------------------------
Observations 30 30
R2 0.692 0.713
Adjusted R2 0.657 0.680
Residual Std. Error (df = 26) 7.134 6.884
F Statistic (df = 3; 26) 19.478*** 21.559***
==========================================================
Note: *p<0.1; **p<0.05; ***p<0.01
答案 1 :(得分:1)
以下回应:
reg ~ felm(....)
rownames(reg$coefficients)[rownames(reg$coefficients)=='oldname']<-'newname'
rownames(reg$beta)[rownames(reg$beta)=='oldname']<-'newname'
似乎适用于大多数情况。
尽管我有时会遇到问题。当felm与IV一起使用时,这是必需的。区分带IV和不带IV的变量虽然很好,但与其他模型相比,这些表会很麻烦!这样的语法将很有帮助。
答案 2 :(得分:0)
万一有人想知道,我出于felm
软件包的其他目的而需要它。为此,需要以下代码:
reg ~ felm(....)
rownames(reg$coefficients)[rownames(reg$coefficients)=='oldname']<-'newname'
rownames(reg$beta)[rownames(reg$beta)=='oldname']<-'newname'