对“系数"进行排序StepAIC 的表格 [英] Sorting the "Coefficients" table of a StepAIC

问题描述

有没有办法对 StepAIC 的系数"部分的输出进行排序(通过估计或 t 值)?

Is there any way to sort the output of the "Coefficients" part of a StepAIC (by estimate or t-value)?

> summary(sta9);

Call:
lm(formula = rating ~ `b/d` + `v/w` + `korte klank` + `lange klank` + 
    `-eer, -oor, -eur` + `-aai, -ooi, -oei` + `-eeuw, -ieuw, -uw` + 
    `-ng` + `-nk` + schwa + `eind d` + `eind b` + open + gesloten + 
    `-ee` + `mv klinker 's` + tussenletter + hoofdletter + trema + 
    regelverkleinwoorden + `-ch, -cht` + `ei/ij` + `ou, au, ouw, auw` + 
    `-sch, -schr` + `i/ie` + `be-, ge-, ver-` + e + `-lijk` + 
    `-heid` + `-teit` + `-tie` + `-ge` + verklein + `-er, -el, -en, -em` + 
    leenwoord + `-air` + `c/k, c/s` + q + x + y + `-th` + accent + 
    ch + length + freq - 1, data = as.data.frame(scale(items16[c(7, 
    21:78, 85:86)])))

Residuals:
    Min      1Q  Median      3Q     Max 
-1.8271 -0.3729 -0.0522  0.3585  1.9980 

Coefficients:
                      Estimate Std. Error t value Pr(>|t|)    
`b/d`                 0.026588   0.009423   2.822 0.004805 ** 
`v/w`                 0.032920   0.009350   3.521 0.000435 ***
`korte klank`        -0.029310   0.013324  -2.200 0.027885 *  
`lange klank`        -0.024760   0.010828  -2.287 0.022271 *  
`-eer, -oor, -eur`   -0.020068   0.009321  -2.153 0.031378 *  
`-aai, -ooi, -oei`    0.015499   0.009259   1.674 0.094217 .  
`-eeuw, -ieuw, -uw`   0.019706   0.010097   1.952 0.051045 .  
`-ng`                -0.045828   0.009522  -4.813 1.55e-06 ***
`-nk`                -0.022971   0.009299  -2.470 0.013543 *  
schwa                -0.014353   0.009340  -1.537 0.124461    
`eind d`              0.033766   0.010208   3.308 0.000950 ***
`eind b`              0.041695   0.009045   4.610 4.18e-06 ***
open                  0.042792   0.010284   4.161 3.24e-05 ***
gesloten              0.088218   0.009863   8.944  < 2e-16 ***
`-ee`                 0.014626   0.009043   1.617 0.105879    
`mv klinker 's`       0.012957   0.009101   1.424 0.154628    
tussenletter         -0.052541   0.009850  -5.334 1.02e-07 ***
hoofdletter           0.097015   0.009283  10.451  < 2e-16 ***
trema                 0.141985   0.009932  14.296  < 2e-16 ***
regelverkleinwoorden  0.031238   0.010874   2.873 0.004093 ** 
`-ch, -cht`          -0.044193   0.009947  -4.443 9.15e-06 ***
`ei/ij`               0.041017   0.011251   3.646 0.000271 ***
`ou, au, ouw, auw`    0.021683   0.010342   2.097 0.036092 *  
`-sch, -schr`        -0.055558   0.009299  -5.974 2.54e-09 ***
`i/ie`                0.043021   0.010286   4.182 2.95e-05 ***
`be-, ge-, ver-`     -0.022401   0.009356  -2.394 0.016705 *  
e                     0.051668   0.012349   4.184 2.93e-05 ***
`-lijk`              -0.032245   0.009964  -3.236 0.001222 ** 
`-heid`              -0.075044   0.010324  -7.269 4.42e-13 ***
`-teit`              -0.018272   0.009826  -1.860 0.063034 .  
`-tie`               -0.013415   0.009448  -1.420 0.155715    
`-ge`                -0.019328   0.009757  -1.981 0.047673 *  
verklein             -0.077275   0.012170  -6.350 2.42e-10 ***
`-er, -el, -en, -em` -0.046764   0.009867  -4.739 2.23e-06 ***
leenwoord             0.117488   0.009910  11.856  < 2e-16 ***
`-air`                0.036930   0.009062   4.075 4.69e-05 ***
`c/k, c/s`            0.091685   0.009851   9.307  < 2e-16 ***
q                     0.052842   0.009360   5.645 1.77e-08 ***
x                     0.045299   0.009039   5.011 5.67e-07 ***
y                     0.063955   0.009375   6.822 1.05e-11 ***
`-th`                 0.038773   0.009380   4.134 3.65e-05 ***
accent                0.072422   0.009434   7.677 2.09e-14 ***
ch                    0.029126   0.009621   3.027 0.002484 ** 
length                0.681405   0.013451  50.658  < 2e-16 ***
freq                 -0.025164   0.009157  -2.748 0.006026 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.5466 on 3597 degrees of freedom
  (71 observations deleted due to missingness)
Multiple R-squared: 0.6963, Adjusted R-squared: 0.6925 
F-statistic: 183.3 on 45 and 3597 DF,  p-value: < 2.2e-16

我已经发现这个

sort(sta9$coefficients, decreasing = T);

有效，但它只给我估计"列...

works, but it only gives me the "Estimate" column...

推荐答案

这是一个线性回归示例，可以满足您的需求:

Here is a linear regression example that does what you want:

set.seed(1)
y = rnorm(10);x1 = rnorm(10);x2 = rnorm(10)
m = lm(y ~ x1+ x2)

s = summary(m)
sc = as.data.frame(s$coefficients)

sc[with(sc, order(-Estimate)), ]

这给出:

R> sc[with(sc, order(-Estimate)), ]
            Estimate Std. Error t value Pr(>|t|)
x1           0.06398     0.2405  0.2661  0.79785
(Intercept)  0.03234     0.2128  0.1519  0.88352
x2          -0.62799     0.2691 -2.3332  0.05236

您的主要问题是您使用了来自 sta9 的系数向量，而不是由 summary 命令生成的表，即比较:

Your main problem was that you used the coefficients vector from sta9 instead of the table produced by the summary command, i.e. compare:

sta9$coefficients

与

summary(sta9)$coefficients

这篇关于对“系数"进行排序StepAIC 的表格的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！