[R] t-test for regression estimate

[BONACHE Adrien]

Dear Steven,
I understand your request now. Maybe you could try to change the function lm and create another function enabling you to have the information you want really quickly. 
Use lm() to see the code of this command and change this one marginally to get what you want to. Once this is done, copy paste the code in a new function and save your code.
Regards,
Adrien.
      De : Steven Yen <syen04 at gmail.com>
 À : "Fox, John" <jfox at mcmaster.ca> 
Cc : R-help <r-help at r-project.org>
 Envoyé le : Mercredi 29 juin 2016 0h43
 Objet : Re: [R] t-test for regression estimate
   
Thanks John. Reason is I am doing linear transformations of many 
coefficients (e.g., bi / scalar). Of course I can uncover the 
t-statistic from the F statistic and then the standard error. Simply 
scaling the estimated coefficients I can also transform the standard 
errors. I have since found deltaMethod from library "car" useful. Its 
just that, if linearHypothesis had provide the standard errors and 
t-statistics then the operation would have been easier, with a one-line 
command for each coefficient. Thank you again.

On 6/28/2016 6:28 PM, Fox, John wrote:
> Dear Steven,
>
> The reason that linearHypothesis() computes a Wald F or chisquare test rather than a t or z test is that the (numerator) df for the linear hypothesis need not be 1.
>
> In your case (as has been pointed out) you can get the coefficient standard error directly from the model summary.
>
> More generally, with some work, you could solve for the the SE for a 1 df linear hypothesis in terms of the value of the linear function of coefficients and the F or chisquare. That said, I'm not sure why you want to do this.
>
> I hope this helps,
>  John
>
> -----------------------------
> John Fox, Professor
> McMaster University
> Hamilton, Ontario
> Canada L8S 4M4
> Web: socserv.mcmaster.ca/jfox
>
>
>> -----Original Message-----
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Steven Yen
>> Sent: June 28, 2016 9:27 AM
>> To: R-help <r-help at r-project.org>
>> Subject: [R] t-test for regression estimate
>>
>> test option for linearHypothesis in library(car) include "Chisq" and "F". I prefer
>> a simple t-test so that I can retrieve the standard error.
>> Any options other than linearHypothesis to test the linear hypothesis (with 1
>> restriction/degree of freedom)?
>>
>>  > summary(ols1)
>>
>> Coefficients:
>>              Estimate Std. Error t value Pr(>|t|)
>> (Intercept) -0.20013    0.09199  -2.176  0.0298 *
>> age          0.04054    0.01721  2.355  0.0187 *
>> suburb      0.01911    0.05838  0.327  0.7435
>> smcity      -0.29969    0.19175  -1.563  0.1184
>> ---
>> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>>
>>  > linearHypothesis(ols1,"suburb")
>> Linear hypothesis test
>>
>> Hypothesis:
>> suburb = 0
>>
>> Model 1: restricted model
>> Model 2: polideo ~ age + suburb + smcity
>>
>>    Res.Df    RSS Df Sum of Sq      F Pr(>F)
>> 1    888 650.10
>> 2    887 650.02  1  0.078534 0.1072 0.7435
>>
>>
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>>
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