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:sye...@gmail.com]
>> Sent: June 28, 2016 3:44 PM
>> To: Fox, John <j...@mcmaster.ca>
>> Cc: R-help <r-help@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-boun...@r-project.org] On Behalf
>> Of Steven Yen
>> Sent: June 28, 2016 9:27 AM
>> To: R-help <r-help@r-project.org> <mailto:r-help@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]]
>>
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>> R-help@r-project.org <mailto:R-help@r-project.org> mailing
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>> PLEASE do read the posting guide http://www.R-
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>> and provide commented, minimal, self-contained, reproducible
>> code.
>>
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