解决在 R 中使用 stargazer 创建 table logit 回归结果的错误
Resolve error in creating table of logit regression results with stargazer in R
我希望展示一个很好的 table 使用 stargazer 测量高血压的逻辑回归,其中包括系数、标准误差和显着性(用星号表示)。当我尝试插入 stargazer 的规范时,我看到以下错误消息:“% 错误:无法识别的对象类型。”我在下面 运行 包含了一些示例 data/the 代码。这将如何解决?谢谢!
library(stargazer)
library(mfx)
structure(list(AGE = c(40L, 23L, 24L, 18L, 30L, 33L, 32L, 63L,
22L, 24L), IMMIGRANT = c(0, 0, 0, 0, 0, 1, 0, 0, 0, 1), FAMSIZE = c(2L,
2L, 2L, 3L, 2L, 6L, 2L, 1L, 2L, 1L), HLTH_INS = c(1, 1, 1, 1,
1, 0, 1, 1, 1, 0), HYPERTEN = c(0, 0, 0, 0, 0, 0, 0, 1, 0, 0),
SMOKE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1), PSU = c(2L, 1L,
2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L)), row.names = c(NA, -10L), class = "data.frame")
#The regression works without adjusting for clustered SE
logit<-logitmfx(HYPERTEN~AGE+IMMIGRANT+FAMSIZE+HLTH_INS+
SMOKE,data=sample,
atmean=TRUE,robust=T)
logit_mfx_coef <- logit$mfxest[,1]
logit_mfx_se <- logit$mfxest[,2]
stargazer(logit, type="text",title = "Predicting Probability of Hypertension",intercept.bottom=FALSE,
coef = logit_mfx_coef,
se = logit_mfx_coef, column.labels="Logit mfx",
digits=4,align=TRUE)
将 logit$fit
作为第一个参数传递给 stargazer()
。
logitmfx()
operation returns a bunch of stuff, but stargazer()
需要一个拟合模型对象(或数据框)作为它的第一个参数。
stargazer(logit$fit, type="text",title = "Predicting Probability of Hypertension",intercept.bottom=FALSE,
coef = logit_mfx_coef,
se = logit_mfx_coef, column.labels="Logit mfx",
digits=4,align=TRUE)
输出:
Predicting Probability of Hypertension
=============================================
Dependent variable:
---------------------------
HYPERTEN
Logit mfx
---------------------------------------------
Constant 0.0000
(0.0000)
AGE
IMMIGRANT
FAMSIZE
HLTH_INS
SMOKE
---------------------------------------------
Observations 10
Log Likelihood -0.0000
Akaike Inf. Crit. 10.0000
=============================================
Note: *p<0.1; **p<0.05; ***p<0.01
我希望展示一个很好的 table 使用 stargazer 测量高血压的逻辑回归,其中包括系数、标准误差和显着性(用星号表示)。当我尝试插入 stargazer 的规范时,我看到以下错误消息:“% 错误:无法识别的对象类型。”我在下面 运行 包含了一些示例 data/the 代码。这将如何解决?谢谢!
library(stargazer)
library(mfx)
structure(list(AGE = c(40L, 23L, 24L, 18L, 30L, 33L, 32L, 63L,
22L, 24L), IMMIGRANT = c(0, 0, 0, 0, 0, 1, 0, 0, 0, 1), FAMSIZE = c(2L,
2L, 2L, 3L, 2L, 6L, 2L, 1L, 2L, 1L), HLTH_INS = c(1, 1, 1, 1,
1, 0, 1, 1, 1, 0), HYPERTEN = c(0, 0, 0, 0, 0, 0, 0, 1, 0, 0),
SMOKE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1), PSU = c(2L, 1L,
2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L)), row.names = c(NA, -10L), class = "data.frame")
#The regression works without adjusting for clustered SE
logit<-logitmfx(HYPERTEN~AGE+IMMIGRANT+FAMSIZE+HLTH_INS+
SMOKE,data=sample,
atmean=TRUE,robust=T)
logit_mfx_coef <- logit$mfxest[,1]
logit_mfx_se <- logit$mfxest[,2]
stargazer(logit, type="text",title = "Predicting Probability of Hypertension",intercept.bottom=FALSE,
coef = logit_mfx_coef,
se = logit_mfx_coef, column.labels="Logit mfx",
digits=4,align=TRUE)
将 logit$fit
作为第一个参数传递给 stargazer()
。
logitmfx()
operation returns a bunch of stuff, but stargazer()
需要一个拟合模型对象(或数据框)作为它的第一个参数。
stargazer(logit$fit, type="text",title = "Predicting Probability of Hypertension",intercept.bottom=FALSE,
coef = logit_mfx_coef,
se = logit_mfx_coef, column.labels="Logit mfx",
digits=4,align=TRUE)
输出:
Predicting Probability of Hypertension
=============================================
Dependent variable:
---------------------------
HYPERTEN
Logit mfx
---------------------------------------------
Constant 0.0000
(0.0000)
AGE
IMMIGRANT
FAMSIZE
HLTH_INS
SMOKE
---------------------------------------------
Observations 10
Log Likelihood -0.0000
Akaike Inf. Crit. 10.0000
=============================================
Note: *p<0.1; **p<0.05; ***p<0.01