Dear Steven,

> -----Original Message-----
> From: Steven Yen [mailto:sye...@gmail.com]
> Sent: June 29, 2016 9:48 AM
> To: Fox, John <j...@mcmaster.ca>
> Cc: R-help <r-help@r-project.org>; Sandy Weisberg (sa...@umn.edu)
> <sa...@umn.edu>
> Subject: Re: [R] t-test for regression estimate
> 
> Also,
> Is there a way to get the second command (hypothesis defined with externally
> scalars) below to work? Thanks.
> 
> linearHypothesis(U,"0.5*eq1_DQ+0.3*eq2_DQ",verbose=T)
> w1<-0.5; w2<-0.3
> linearHypothesis(U,"w1*eq1_DQ+w2*eq2_DQ",verbose=T) # does not work

You can specify the hypothesis matrix (a vector in the 1-df case). E.g.,

----------------- snip ---------------------    

> library(car)
> mod <- lm(prestige ~ income + education, data=Duncan)
> one <- 1
> minus.one <- -1
> linearHypothesis(mod, c(0, one, minus.one)) # 0 * the intercept
Linear hypothesis test

Hypothesis:
income - education = 0

Model 1: restricted model
Model 2: prestige ~ income + education

  Res.Df    RSS Df Sum of Sq      F Pr(>F)
1     43 7518.9                           
2     42 7506.7  1    12.195 0.0682 0.7952

----------------- snip ---------------------    

John

> 
> 
> On 6/29/2016 12:38 PM, Steven Yen wrote:
> 
> 
>       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" <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>
> <mailto:j...@mcmaster.ca>
>                       Cc: R-help <r-help@r-project.org> <mailto: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>  <mailto: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
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> 
> 
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> 

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