[R] Format regression result summary

[Chuck Cleland]

On 4/11/2008 12:05 PM, Thiemo Fetzer wrote:
> Hello to the whole group.
> 
> I am a newbie to R, but I got my way through and think it is a lot easier to
> handle than other software packages (far less clicks necessary).
> 
> However, I have a problem with respect to the summary of regression results.
> 
> The summary function gives sth like:
> 
> Residuals:
>      Min       1Q   Median       3Q      Max 
> -0.46743 -0.09772  0.01810  0.11175  0.42252 
> 
> Coefficients:
>                              Estimate Std. Error t value Pr(>|t|)    
> (Intercept)                  3.750367   0.172345  21.761  < 2e-16 ***
> Var1	                      -0.002334   0.009342  -0.250 0.802948    
> Var2				     0.012551   0.005927   2.117 0.035444 *
> 
> Var3	 		           0.015380   0.074537   0.206 0.836730    
> Var3	                       0.098602   0.026448   3.728 0.000250 ***
> ...
> 
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> 
> Residual standard error: 0.1614 on 202 degrees of freedom
> Multiple R-squared: 0.1983,     Adjusted R-squared: 0.1506 
> F-statistic: 4.163 on 12 and 202 DF,  p-value: 7.759e-06
> 
> However, my wish is the output to have a format like:
> 
>                              Estimate 
> (Intercept)                  3.750367*** 
> 					(0.172345)
> Var1	                      -0.002334
> 					(0.009342)    
> Var2				     0.012551*
> 					(0.005927)
> 
> Etc. so that the standard errors are in parantheses below the estimates.
> Next to the estimates should be the * indicating significance.
> 
> I thought that should go by accessing the elements in the summary object,
> yet, I got started and figured that is quite complicated. 
> 
> Is there a quick and dirty way? 
> Basically I want the same print-out as the summary, except that I don't want
> the t-statistic and not the p-value, only the significance codes.

   The mtable function in the memisc package by Martin Elff comes pretty 
close to what you want:

library(memisc)

(mtable123 <- mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2))

Calls:
Model 1: lm(formula = sr ~ pop15 + pop75, data = LifeCycleSavings)
Model 2: lm(formula = sr ~ dpi + ddpi, data = LifeCycleSavings)
Model 3: lm(formula = sr ~ pop15 + pop75 + dpi + ddpi, data = 
LifeCycleSavings)

==================================================
                  Model 1     Model 2     Model 3
--------------------------------------------------
Coefficients
(Intercept)      30.628***    6.360***   28.566***
                  (7.409)     (1.252)     (7.355)
pop15            -0.471**                -0.461**
                  (0.147)                 (0.145)
pop75            -1.934                  -1.691
                  (1.041)                 (1.084)
dpi                           0.001      -0.000
                              (0.001)     (0.001)
ddpi                          0.529*      0.410*
                              (0.210)     (0.196)
--------------------------------------------------
Summaries
R-squared         0.262       0.162       0.338
adj. R-squared    0.230       0.126       0.280
sigma             3.931       4.189       3.803
F                 8.3         4.5         5.8
p                 0.001       0.016       0.001
Log-likelihood -137.8      -141.0      -135.1
Deviance        726.2       824.7       650.7
AIC             283.7       290.0       282.2
BIC             291.3       297.7       293.7
N                50          50          50
==================================================

> Thanks a lot in advance
> 
> Thiemo
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code. 

-- 
Chuck Cleland, Ph.D.
NDRI, Inc. (www.ndri.org)
71 West 23rd Street, 8th floor
New York, NY 10010
tel: (212) 845-4495 (Tu, Th)
tel: (732) 512-0171 (M, W, F)
fax: (917) 438-0894