我知道这polr不会给出 p 值，因为它们不是很可靠。不过，我想将它们添加到我的modelsummary( Vignette ) 输出中。我知道要获得如下值：
library(MASS)
polr_res <- polr(as.ordered(rep77) ~ foreign + length + mpg, Hess=TRUE, data=fullauto);summary(polr_res)
Call:
polr_res(formula = as.ordered(rep77) ~ foreign + length + mpg, data = fullauto,
Hess = TRUE)
## coefficient test
library("AER")
coeftest(polr_res)
模型总结
因为polr没有 p 值，所以我不能调用modelsummary(models, stars=TRUE)我的models（包括其他具有 p 值并且我想为其显示星星的模型）。
library(modelsummary)
models <- list(
"Ordinal Probit" = polr_res,
)
# model_names <- c("OLS", "")
modelsummary(models, stars=TRUE)
我首先尝试简单地将 p 值添加到tidy对象中，但我无法将该对象添加到models.
polr_pval <- coeftest(polr)[,4]
polr_pval <- as.data.frame(polr_pval)
tidy_polr <- tidy(polr)
tidy_polr[,5] <- polr_pval
小插图描述了我可以制作一个适应polr.
谁能帮我解决这个问题？
编辑：
我正在发布一个编辑，显示我在使用文森特的答案时遇到的问题，使用R version 3.6.1 (2019-07-05). 如果您遇到此问题，（最好）更新到 R 版本 4.0.0 或modelsummary从 Github 下载更新（另请参阅下面文森特的评论）。：
library(remotes)
remotes::install_github('vincentarelbundock/modelsummary')
输出：
R的数据
fullauto <- structure(list(make = structure(c(1, 1, 1, 2, 2, 3, 4, 4, 4,
4, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8,
9, 10, 10, 11, 11, 12, 12, 12, 13, 14, 14, 14, 14, 14, 14, 15,
15, 15, 15, 15, 15, 15, 16, 17, 17, 17, 17, 17, 18, 18, 18, 18,
18, 18, 19, 20, 21, 21, 21, 22, 22, 22, 22, 23), label = "Make", format.stata = "%8.0g", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(AMC = 1, Audi = 2, BMW = 3,
Buick = 4, Cad. = 5, Chev. = 6, Datsun = 7, Dodge = 8, Fiat = 9,
Ford = 10, Honda = 11, Linc. = 12, Mazda = 13, Merc. = 14, Olds = 15,
Peugeot = 16, Plym. = 17, Pont. = 18, Renault = 19, Subaru = 20,
Toyota = 21, VW = 22, Volvo = 23)), model = structure(c(1, 2,
3, 4, 5000, 320, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 200, 210, 510, 810, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
45, 98, 604, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57,
58, 59, 60, 61, 62, 63, 64, 65, 260), label = "Model", format.stata = "%8.0g", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(Concord = 1, Pacer = 2, Spirit = 3,
Fox = 4, Century = 5, Electra = 6, LeSabre = 7, Opel = 8, Regal = 9,
Riviera = 10, Skylark = 11, Deville = 12, Eldrado = 13, Seville = 14,
Chevette = 15, Impala = 16, Malibu = 17, MCarlo = 18, Monza = 19,
Nova = 20, Colt = 21, Diplomat = 22, Magnum = 23, StRegis = 24,
Strada = 25, Fiesta = 26, Mustang = 27, Accord = 28, Civic = 29,
Cntntl = 30, `Mark V` = 31, Vrsills = 32, GLC = 33, Bobcat = 34,
Cougar = 35, `XR-7` = 36, Marquis = 37, Monarch = 38, Zephyr = 39,
Cutlass = 40, CutlSupr = 41, `Delta 88` = 42, Omega = 43, Starfire = 44,
Toronado = 45, Arrow = 46, Champ = 47, Horizon = 48, Sapporo = 49,
Volare = 50, Catalina = 51, Firebird = 52, GranPrix = 53, `Le Mans` = 54,
Phoenix = 55, Sunbird = 56, `Le Car` = 57, Subaru = 58, Celica = 59,
Corolla = 60, Corona = 61, Rabbit = 62, Diesel = 63, Scirocco = 64,
Dasher = 65)), price = structure(c(4099, 4749, 3799, 6295, 9690,
9735, 4816, 7827, 5788, 4453, 5189, 10372, 4082, 11385, 14500,
15906, 3299, 5705, 4504, 5104, 3667, 3955, 6229, 4589, 5079,
8129, 3984, 4010, 5886, 6342, 4296, 4389, 4187, 5799, 4499, 11497,
13594, 13466, 3995, 3829, 5379, 6303, 6165, 4516, 3291, 4733,
5172, 4890, 4181, 4195, 10371, 8814, 12990, 4647, 4425, 4482,
6486, 4060, 5798, 4934, 5222, 4723, 4424, 4172, 3895, 3798, 5899,
3748, 5719, 4697, 5397, 6850, 7140, 11995), label = "Price", format.stata = "%8.0g"),
mpg = structure(c(22, 17, 22, 23, 17, 25, 20, 15, 18, 26,
20, 16, 19, 14, 14, 21, 29, 16, 22, 22, 24, 19, 23, 35, 24,
21, 30, 18, 16, 17, 21, 28, 21, 25, 28, 12, 12, 14, 30, 22,
14, 14, 15, 18, 20, 19, 19, 18, 19, 24, 16, 21, 14, 38, 34,
25, 26, 18, 18, 18, 19, 19, 19, 24, 26, 35, 18, 31, 18, 25,
41, 25, 23, 17), label = "Mileage (mpg)", format.stata = "%8.0g"),
rep78 = structure(c(3, 3, NA, 3, 5, 4, 3, 4, 3, NA, 3, 3,
3, 3, 2, 3, 3, 4, 3, 2, 2, 3, 4, 5, 4, 4, 5, 2, 2, 2, 3,
4, 3, 5, 4, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 4, 3, 1,
3, 4, NA, 3, 5, 3, NA, 2, 4, 1, 3, 3, NA, 2, 3, 5, 5, 5,
5, 4, 5, 4, 4, 5), label = "Repair Record 1978", format.stata = "%9.0g", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(Poor = 1, Fair = 2, Average = 3,
Good = 4, Excellent = 5)), rep77 = structure(c(2, 1, NA,
3, 2, 4, 3, 4, 4, NA, 3, 4, 3, 3, 2, 3, 3, 4, 3, 3, 2, 3,
3, 5, 4, 4, 4, 2, 2, 2, 1, NA, 3, 5, 4, 4, 4, 3, 4, 3, 3,
4, 2, NA, 3, 3, 4, 4, 3, 1, 3, 4, NA, 3, 4, NA, NA, 2, 4,
2, 3, 3, NA, 2, 3, 4, 5, 5, 5, 3, 4, 3, 3, 3), label = "Repair Record 1977", format.stata = "%9.0g", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(Poor = 1, Fair = 2, Average = 3,
Good = 4, Excellent = 5)), hdroom = structure(c(2.5, 3, 3,
2.5, 3, 2.5, 4.5, 4, 4, 3, 2, 3.5, 3.5, 4, 3.5, 3, 2.5, 4,
3.5, 2, 2, 3.5, 1.5, 2, 2.5, 2.5, 2, 4, 4, 4.5, 2.5, 1.5,
2, 3, 2.5, 3.5, 2.5, 3.5, 3.5, 3, 3.5, 3, 3.5, 3, 3.5, 4.5,
2, 4, 4.5, 2, 3.5, 4, 3.5, 2, 2.5, 4, 1.5, 5, 4, 1.5, 2,
3.5, 3.5, 2, 3, 2.5, 2.5, 3, 2, 3, 3, 2, 2.5, 2.5), label = "Headroom (in.)", format.stata = "%6.1f"),
rseat = structure(c(27.5, 25.5, 18.5, 28, 27, 26, 29, 31.5,
30.5, 24, 28.5, 30, 27, 31.5, 30, 30, 26, 29.5, 28.5, 28.5,
25, 27, 21, 23.5, 22, 27, 24, 29, 29, 28, 26.5, 26, 23, 25.5,
23.5, 30.5, 28.5, 27, 25.5, 25.5, 29.5, 25, 30.5, 27, 29,
28, 28, 29, 27, 25.5, 30, 31.5, 30.5, 21.5, 23, 25, 22, 31,
29, 23.5, 28.5, 28, 27, 25, 23, 25.5, 22, 24.5, 23, 25.5,
25.5, 23.5, 37.5, 29.5), label = "Rear Seat (in.)", format.stata = "%6.1f"),
trunk = structure(c(11, 11, 12, 11, 15, 12, 16, 20, 21, 10,
16, 17, 13, 20, 16, 13, 9, 20, 17, 16, 7, 13, 6, 8, 8, 8,
8, 17, 17, 21, 16, 9, 10, 10, 5, 22, 18, 15, 11, 9, 16, 16,
23, 15, 17, 16, 16, 20, 14, 10, 17, 20, 14, 11, 11, 17, 8,
16, 20, 7, 16, 17, 13, 7, 10, 11, 14, 9, 11, 15, 15, 16,
12, 14), label = "Trunk space (cu. ft.)", format.stata = "%8.0g"),
weight = structure(c(2930, 3350, 2640, 2070, 2830, 2650,
3250, 4080, 3670, 2230, 3280, 3880, 3400, 4330, 3900, 4290,
2110, 3690, 3180, 3220, 2750, 3430, 2370, 2020, 2280, 2750,
2120, 3600, 3600, 3740, 2130, 1800, 2650, 2240, 1760, 4840,
4720, 3830, 1980, 2580, 4060, 4130, 3720, 3370, 2830, 3300,
3310, 3690, 3370, 2730, 4030, 4060, 3420, 3260, 1800, 2200,
2520, 3330, 3700, 3470, 3210, 3200, 3420, 2690, 1830, 2050,
2410, 2200, 2670, 1930, 2040, 1990, 2160, 3170), label = "Weight (lbs.)", format.stata = "%8.0g"),
length = structure(c(186, 173, 168, 174, 189, 177, 196, 222,
218, 170, 200, 207, 200, 221, 204, 204, 163, 212, 193, 200,
179, 197, 170, 165, 170, 184, 163, 206, 206, 220, 161, 147,
179, 172, 149, 233, 230, 201, 154, 169, 221, 217, 212, 198,
195, 198, 198, 218, 200, 180, 206, 220, 192, 170, 157, 165,
182, 201, 214, 198, 201, 199, 203, 179, 142, 164, 174, 165,
175, 155, 155, 156, 172, 193), label = "Length (in.)", format.stata = "%8.0g"),
turn = structure(c(40, 40, 35, 36, 37, 34, 40, 43, 43, 34,
42, 43, 42, 44, 43, 45, 34, 43, 31, 41, 40, 43, 35, 32, 34,
38, 35, 46, 46, 46, 36, 33, 43, 36, 34, 51, 48, 41, 33, 39,
48, 45, 44, 41, 43, 42, 42, 42, 43, 40, 43, 43, 38, 37, 37,
36, 38, 44, 42, 42, 45, 40, 43, 41, 34, 36, 36, 35, 36, 35,
35, 36, 36, 37), label = "Turn Circle (ft.) ", format.stata = "%8.0g"),
displ = structure(c(121, 258, 121, 97, 131, 121, 196, 350,
231, 304, 196, 231, 231, 425, 350, 350, 231, 250, 200, 200,
151, 250, 119, 85, 119, 146, 98, 318, 318, 225, 105, 98,
140, 107, 91, 400, 400, 302, 86, 140, 302, 302, 302, 250,
140, 231, 231, 231, 231, 151, 350, 350, 163, 156, 86, 105,
119, 225, 231, 231, 231, 231, 231, 151, 79, 97, 134, 97,
134, 89, 90, 97, 97, 163), label = "Displacement (cu. in.)", format.stata = "%8.0g"),
gratio = structure(c(3.57999992370605, 2.52999997138977,
3.07999992370605, 3.70000004768372, 3.20000004768372, 3.64000010490417,
2.9300000667572, 2.41000008583069, 2.73000001907349, 2.86999988555908,
2.9300000667572, 2.9300000667572, 3.07999992370605, 2.27999997138977,
2.19000005722046, 2.24000000953674, 2.9300000667572, 2.55999994277954,
2.73000001907349, 2.73000001907349, 2.73000001907349, 2.55999994277954,
3.89000010490417, 3.70000004768372, 3.53999996185303, 3.54999995231628,
3.53999996185303, 2.47000002861023, 2.47000002861023, 2.94000005722046,
3.36999988555908, 3.15000009536743, 3.07999992370605, 3.04999995231628,
3.29999995231628, 2.47000002861023, 2.47000002861023, 2.47000002861023,
3.73000001907349, 2.73000001907349, 2.75, 2.75, 2.25999999046326,
2.4300000667572, 3.07999992370605, 2.9300000667572, 2.9300000667572,
2.73000001907349, 3.07999992370605, 2.73000001907349, 2.41000008583069,
2.41000008583069, 3.57999992370605, 3.04999995231628, 2.97000002861023,
3.36999988555908, 3.53999996185303, 3.23000001907349, 2.73000001907349,
3.07999992370605, 2.9300000667572, 2.9300000667572, 3.07999992370605,
2.73000001907349, 3.72000002861023, 3.80999994277954, 3.05999994277954,
3.21000003814697, 3.04999995231628, 3.77999997138977, 3.77999997138977,
3.77999997138977, 3.74000000953674, 2.98000001907349), label = "Gear Ratio", format.stata = "%6.2f"),
order = structure(c(1, 2, 3, 5, 4, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42,
43, 44, 45, 47, 48, 49, 50, 51, 52, 46, 53, 54, 55, 56, 57,
58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74), label = "Original order", format.stata = "%8.0g"),
foreign = structure(c(0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1,
0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1), label = "Foreign", format.stata = "%8.0g", class = c("haven_labelled",
"vctrs_vctr", "double"), labels = c(Domestic = 0, Foreign = 1
)), wgtd = structure(c(2930, 3350, 2640, NA, NA, NA, 3250,
4080, 3670, 2230, 3280, 3880, 3400, 4330, 3900, 4290, 2110,
3690, 3180, 3220, 2750, 3430, NA, NA, NA, NA, 2120, 3600,
3600, 3740, NA, 1800, 2650, NA, NA, 4840, 4720, 3830, NA,
2580, 4060, 4130, 3720, 3370, 2830, 3300, 3310, 3690, 3370,
2730, 4030, 4060, NA, 3260, 1800, 2200, 2520, 3330, 3700,
3470, 3210, 3200, 3420, 2690, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), format.stata = "%9.0g"), wgtf = structure(c(NA,
NA, NA, 2070, 2830, 2650, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 2370, 2020, 2280, 2750, NA,
NA, NA, NA, 2130, NA, NA, 2240, 1760, NA, NA, NA, 1980, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3420, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1830, 2050, 2410,
2200, 2670, 1930, 2040, 1990, 2160, 3170), format.stata = "%9.0g")), label = "Automobile Models", row.names = c(NA,
-74L), class = c("tbl_df", "tbl", "data.frame"))
