Re: [R] Format regression result summary

From: Chuck Cleland <ccleland_at_optonline.net>
Date: Fri, 11 Apr 2008 12:18:40 -0400

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
>
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.

-- 
Chuck Cleland, Ph.D.
NDRI, Inc. (www.ndri.org)
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New York, NY 10010
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Received on Fri 11 Apr 2008 - 16:35:23 GMT

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