如何在R中的线性回归模型的stargazer输出中显示带有系数的p值？

Z时代
2024-01-10
分类：综合

要在线性回归模型的 stargazer 输出中显示 p 值，我们可以使用 report 参数。例如，如果我们有一个名为 RegressionModel 的模型，那么可以使用以下命令来显示带有系数的 p 值 -

stargazer(RegressionModel,type="text",report=("vc*p"))

示例

考虑以下数据框 -

x1<-rpois(20,1)
x2<-rpois(20,1)
x3<-rpois(20,2)
y1<-rpois(20,10)
df1<-data.frame(x1,x2,x3,y1)
df1

输出结果

x1 x2 x3 y1

1 3 0 2 8

2 1 0 2 11

3 1 1 4 11

4 0 1 1 12

5 0 0 1 14

6 2 1 2 11

7 1 0 2 5

8 0 0 1 15

9 4 1 2 10

10 3 2 0 9

11 3 0 2 10

12 3 1 1 8

13 1 1 0 12

14 1 3 2 4

15 2 3 3 7

16 0 3 2 9

17 0 0 1 8

18 2 0 3 6

19 3 2 0 7

20 0 0 2 12

加载 stargazer 包并创建线性模型，然后使用 p 值找到模型的摘要 -

示例

library(stargazer)
Model1<-lm(y1~x1+x2+x3,data=df1) stargazer(Model1,type="text",report=("vc*p"))

输出结果

===============================================
            Dependent variable:
          ---------------------------
                   y1
-----------------------------------------------
x1             -0.714
             p = 0.143
x2             -0.927
            p = 0.115
x3            -0.610
            p = 0.310
Constant     12.407***
             p = 0.00000
-----------------------------------------------
Observations              20
R2                     0.302
Adjusted R2              0.171
Residual Std. Error   2.634 (df = 16)
F Statistic          2.305 (df = 3; 16)
===============================================

注 - *p<0.1；**p<0.05；*** p<0.01

示例

z1<-rnorm(20)
z2<-rnorm(20)
z3<-rnorm(20)
y2<-rnorm(20,10,3.1)
df2<-data.frame(z1,z2,z3,y2)
df2

输出结果

z1 z2 z3 y2

1 -0.3024865 1.8450469 -0.032156929 14.763669

2 -1.0796487 -1.2162927 1.747917078 16.461999

3 -1.6121022 0.2819740 0.296357366 11.177208

4 1.9958012 -0.1158926 -1.175746738 8.759228

5 -0.1659197 0.3013404 -0.109551154 8.147569

6 -0.9079042 -1.4988982 -0.926541292 13.685437

7 1.1439520 0.4296925 -0.173336829 10.378551

8 -0.8658762 -0.4344171 -0.203837967 15.475533

9 -1.7491852 -1.6852153 -0.025670524 12.039891

10 0.6218240 -1.7620684 1.443519038 14.959877

11 1.5139715 0.1595499 -0.126098531 11.290937

12 -1.4201990 0.9647484 0.466086467 9.191888

13 -1.3909176 0.7077692 -0.388831434 9.950162

14 -0.8915488 -0.2029863 -0.086686050 14.363359

15 2.8241978 -0.8867613 0.855514442 12.082459

16 1.2901426 -0.1418288 -0.005518721 9.116805

17 -0.3083862 -1.5115591 -0.167108671 5.288109

18 -0.7375569 0.7266295 1.044075401 10.463955

19 0.6049541 -0.5745765 1.284913625 8.948373

20 1.0883505 1.2288220 -0.183441449 9.809202

示例

Model2<-lm(y2~z1+z2+z3,data=df2)
stargazer(Model2,type="text",report=("vc*p"))

输出结果

===============================================
             Dependent variable:
          ---------------------------
                    y2
-----------------------------------------------
 z1              -0.453
               p = 0.387
z2               -0.346
               p = 0.612
z3               0.960
              p = 0.306
Constant      11.082***
             p = 0.000
-----------------------------------------------
Observations             20
R2 0.139
Adjusted               R2 -0.023
Residual Std. Error    2.921 (df = 16)
F Statistic            0.860 (df = 3; 16)
===============================================