如何在texreg来电中自定义适合度（gof）？
我想要显示一些plm个模型，但我只获得"Num. obs.", "Adj. R^2",和, "R^2"（请参阅下面的工作示例）。我希望所有显示小n，T，F-statistic和p-value的内容都是我在默认summary()调用中获得的所有内容。
我得到的一个例子。首先是一些数据和所需的包，
# install.packages(c("wooldridge", "plm", "texreg"), dependencies = TRUE)
library(wooldridge)
data(wagepan)
library(plm)
第二，一些模型，
POLS <- plm(lwage ~ educ + black + hisp + exper+I(exper^2)+ married + union +
factor(year), data = wagepan, index=c("nr","year") , model="pooling")
RE <- plm(lwage ~ educ + black + hisp + exper + I(exper^2) + married + union +
factor(year), data = wagepan, index = c("nr","year") , model = "random")
FE <- plm(lwage ~ I(exper^2) + married + union + factor(year),
data = wagepan, index = c("nr","year"), model="within")
第三，我当前的texreg电话及其输出
# library(texreg)
texreg::screenreg(list(POLS, RE, FE), custom.coef.map = list('married' = 'Marrtied', 'union' = 'Union'))
#> ================================================
#> Model 1 Model 2 Model 3
#> ------------------------------------------------
#> Marrtied 0.11 *** 0.06 *** 0.05 *
#> (0.02) (0.02) (0.02)
#> Union 0.18 *** 0.11 *** 0.08 ***
#> (0.02) (0.02) (0.02)
#> ------------------------------------------------
#> R^2 0.19 0.18 0.18
#> Adj. R^2 0.19 0.18 0.06
#> Num. obs. 4360 4360 4360
#> ================================================
#> *** p < 0.001, ** p < 0.01, * p < 0.05
我确实尝试添加, include.fstatistic = TRUE，但似乎我不能这样做。因为我需要一些额外的定制。
我的目标是这样的，
#> ------------------------------------------------
#> Obs. (N) 4360 4360 4360
#> Indiv.(n) 545 545 545
#> Time (T) 8 8 8
#> R^2 0.19 0.18 0.18
#> Adj. R^2 0.19 0.18 0.06
#> F-stat 72.458 68.4124 83.8515
#> P-value (2.22e-16) (2.22e-16) (2.22e-16)
#> ================================================
#> *** p < 0.001, ** p < 0.01, * p < 0.05
答案 0 :(得分：2)
跟进@jaySF的答案，创建你自己的提取函数，它包装了默认值，并注册它：
custom_extract_plm <- function(model, ...) {
s <- summary(model)
ex.1 <- texreg:::extract.plm(model, ...)
fv.1 <- s$fstatistic$statistic
pv.1 <- s$fstatistic$p.value
ex.1@gof.names <- c(ex.1@gof.names, "F-stat", "P-value")
ex.1@gof <- c(ex.1@gof, fv.1, pv.1)
ex.1@gof.decimal <- c(ex.1@gof.decimal, TRUE, TRUE)
ex.1
}
setMethod(texreg:::extract, signature = className("plm", "plm"), custom_extract_plm)
现在你得到一个F统计量：
> texreg::screenreg(list(POLS, RE, FE), custom.coef.map = list('married' = 'Marrtied', 'union' = 'Union'))
================================================
Model 1 Model 2 Model 3
------------------------------------------------
Marrtied 0.11 *** 0.06 *** 0.05 *
(0.02) (0.02) (0.02)
Union 0.18 *** 0.11 *** 0.08 ***
(0.02) (0.02) (0.02)
------------------------------------------------
R^2 0.19 0.18 0.18
Adj. R^2 0.19 0.18 0.06
Num. obs. 4360 4360 4360
F-stat 72.46 68.41 83.85
P-value 0.00 0.00 0.00
================================================
*** p < 0.001, ** p < 0.01, * p < 0.05
答案 1 :(得分：1)
您可以使用texreg::extract()破解它。
获得＆＃34;小n＆＃34;我们首先需要一个小功能。
getIndex <- function(fit){
# extracts number of factor levels of index variables
# from raw data used in models
index.names <- as.character(as.list(summary(fit)$call)$index)[-1]
if (length(index.names == 1)){
df.name <- as.character(as.list(summary(fit)$call)$data)
index.df <- get(df.name)[, index.names]
length(unique(index.df))
}
if (length(index.names == 2)){
df.name <- as.character(as.list(summary(fit)$call)$data)
index.df <- get(df.name)[, index.names]
cbind(length(unique(index.df[, 1])),
length(unique(index.df[, 2])))
} else {
stop("no index variables specified in model")
}
}
然后继续提取。
fv.1 <- summary(POLS)$fstatistic$statistic # get F statistic
pv.1 <- summary(POLS)$fstatistic$p.value # get p value
ns.1 <- getIndex(POLS)[1] # get small n
tm.1 <- getIndex(POLS)[2] # get times
library(texreg)
ex.1 <- extract(POLS) # extract coefficients and GOF measures
ex.1@gof.names <- c(ex.1@gof.names[1:3],"Indiv.(n)", "Time (T)",
"F-stat", "P-value") # the GOF names
ex.1@gof <- c(ex.1@gof[1:3], ns.1, tm.1, fv.1, pv.1) # the GOF values
ex.1@gof.decimal <- c(ex.1@gof.decimal[1:3], FALSE, FALSE, TRUE, TRUE) # numeric or integer
fv.2 <- summary(RE)$fstatistic$statistic
pv.2 <- summary(RE)$fstatistic$p.value
ns.2 <- getIndex(RE)[1]
tm.2 <- getIndex(RE)[2]
ex.2 <- extract(RE)
ex.2@gof.names <- c(ex.2@gof.names[1:3],"Indiv.(n)", "Time (T)",
"F-stat", "P-value")
ex.2@gof <- c(ex.2@gof[1:3], ns.2, tm.2, fv.2, pv.2)
ex.2@gof.decimal <- c(ex.2@gof.decimal[1:3], FALSE, FALSE, TRUE, TRUE)
fv.3 <- summary(FE)$fstatistic$statistic
pv.3 <- summary(FE)$fstatistic$p.value
ns.3 <- getIndex(FE)[1]
tm.3 <- getIndex(FE)[2]
ex.3 <- extract(FE)
ex.3@gof.names <- c(ex.3@gof.names[1:3],"Indiv.(n)", "Time (T)",
"F-stat", "P-value")
ex.3@gof <- c(ex.3@gof[1:3], ns.3, tm.3, fv.3, pv.3)
ex.3@gof.decimal <- c(ex.3@gof.decimal[1:3], FALSE, FALSE, TRUE, TRUE)
<强>屈服
> screenreg(list(ex.1, ex.2, ex.3))
=======================================================
Model 1 Model 2 Model 3
-------------------------------------------------------
[TRUNCATED...]
-------------------------------------------------------
R^2 0.19 0.18 0.18
Adj. R^2 0.19 0.18 0.06
Num. obs. 4360 4360 4360
Indiv.(n) 545 545 545
Time (T) 8 8 8
F-stat 72.46 68.41 83.85
P-value 0.00 0.00 0.00
=======================================================
*** p < 0.001, ** p < 0.01, * p < 0.05
看看例如str(extract(FE))将其用于其他GOF。
要将它包装成函数，请查看@Neal Fultz的答案中的代码。
答案 2 :(得分：1)
这是使用huxreg包中的huxtable的一种可能性。您还需要安装broom软件包。
library(huxtable)
ht <- huxreg(POLS, RE, FE,
coefs = c("Married" = "married", "Union" = "union"),
statistics = c("Obs. (N)" = "nobs", "Adj. R^2" = "adj.r.squared",
"F statistic" = "statistic", "P value" = "p.value"))
时间单位的数量不在broom::glance，因此我们手动添加 - 这是一个简单的方法：
Ts <- purrr::map_int(list(POLS, RE, FE), list(pdim, "nT", "T"))
ns <- purrr::map_int(list(POLS, RE, FE), list(pdim, "nT", "n"))
ht <- insert_row(ht, c("Time (T)", Ts), after = 6)
ht <- insert_row(ht, c("Indiv. (n)", ns), after = 6)
ht
───────────────────────────────────────────────────────────────
(1) (2) (3)
─────────────────────────────────────────────────
Married 0.108 *** 0.064 *** 0.047 *
(0.016) (0.017) (0.018)
Union 0.182 *** 0.106 *** 0.080 ***
(0.017) (0.018) (0.019)
─────────────────────────────────────────────────
Obs. (N) 4360 4360 4360
Indiv. (n) 545 545 545
Time (T) 8 8 8
Adj. R^2 0.187 0.178 0.061
F statistic 72.459 68.412 83.851
P value 7.250e-186 5.813e-176 1.655e-156
───────────────────────────────────────────────────────────────
*** p < 0.001; ** p < 0.01; * p < 0.05.
Column names: names, model1, model2, model3
这将在Rmarkdown文档中自动打印为TeX / HTML。您可以对其进行编辑以添加行，列和进一步格式化。