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 >> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> 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.[[alternative HTML version deleted]]
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>
??: "Fox, John" <jfox at mcmaster.ca>
Cc?: R-help <r-help at r-project.org>
Envoy? 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
>>
>>
>> ??? [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> 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.
??? [[alternative HTML version deleted]]
______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
[[alternative HTML version deleted]]
Dear Steven,
OK -- that makes sense, and there was also a previous request for
linearHypothesis() to return the value of the hypothesis and its covariance
matrix. In your case, where there's only 1 numerator df, that would be the
value and estimated sampling variance of the hypothesis.
I've now implemented that, using (at least provisionally) attributes in the
development version of the car package on R-Forge, which you should be able to
install via install.packages("car",
repos="http://R-Forge.R-project.org"). Then see ?linearHypothesis for
more information.
Best,
John
> -----Original Message-----
> From: Steven Yen [mailto:syen04 at gmail.com]
> Sent: June 28, 2016 3:44 PM
> To: Fox, John <jfox at mcmaster.ca>
> Cc: R-help <r-help at r-project.org>
> Subject: 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> <mailto: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
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org <mailto:R-help at r-project.org> mailing
> list -- To UNSUBSCRIBE and more, see
> 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.
>
Thanks John. Yes, by using verbose=T, I get the value of the hypothesis. But tell me again, how would I get the variance (standard error)? On 6/29/2016 11:56 AM, Fox, John wrote:> Dear Steven, > > OK -- that makes sense, and there was also a previous request for linearHypothesis() to return the value of the hypothesis and its covariance matrix. In your case, where there's only 1 numerator df, that would be the value and estimated sampling variance of the hypothesis. > > I've now implemented that, using (at least provisionally) attributes in the development version of the car package on R-Forge, which you should be able to install via install.packages("car", repos="http://R-Forge.R-project.org"). Then see ?linearHypothesis for more information. > > Best, > John > >> -----Original Message----- >> From: Steven Yen [mailto:syen04 at gmail.com] >> Sent: June 28, 2016 3:44 PM >> To: Fox, John <jfox at mcmaster.ca> >> Cc: R-help <r-help at r-project.org> >> Subject: 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> <mailto: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 >> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at r-project.org <mailto:R-help at r-project.org> mailing >> list -- To UNSUBSCRIBE and more, see >> 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. >>[[alternative HTML version deleted]]