R help - Sep 2012 - Contradictory results between different heteroskedasticity tests

Hi all,

I'm getting contradictory results from bptest and ncvTest on a model
calculated by GLS as:

olslm = lm(log(rr)~log(aloi)*reg*inv, data)
varlm = lm(I(residuals(olslm)^2)~log(aloi)*reg*inv, data)
glslm = lm(log(rr)~log(aloi)*reg*inv, data, weights=1/fitted(varlm))

Testing both olslm and glslm with both ncvTest and bptest gives:
> ncvTest(olslm)
Non-constant Variance Score Test
Variance formula: ~ fitted.values
Chisquare = 46.88206    Df = 1     p = 7.538963e-12
> ncvTest(glslm)
Non-constant Variance Score Test
Variance formula: ~ fitted.values
Chisquare = 0.001466426    Df = 1     p = 0.9694533
> bptest(olslm)
        studentized Breusch-Pagan test
data:  olslm
BP = 213.1477, df = 7, p-value < 2.2e-16
> bptest(glslm)
        studentized Breusch-Pagan test
data:  glslm
BP = 213.1477, df = 7, p-value < 2.2e-16

Please notice the last output. It seems as if bptest is not
considering the weights given to lm. What am I doing wrong here?

Best regards
--
Carlos

Dear Carlos,

Please note that the default alternative hypothesis is different in
ncvTest() and bptest() -- in the former that the error variance is a
function of the expectation of Y (hence the formula ~ fitted.values, with 1
df for the test), and in the latter that the error variance is a function of
a linear combination of the predictors in the model (hence, in your case, 7
df for the test). For testing a different alternative hypothesis with
ncvTest(), see ?ncvTest. 

I won't comment of what bptest() does with the weighted model, but ncvTest()
uses the Pearson residuals and hence takes account of the weights.

I hope this helps,
 John

-----------------------------------------------
John Fox
Senator McMaster Professor of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada



> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org]
> On Behalf Of Carlos Pita
> Sent: Tuesday, September 18, 2012 2:22 PM
> To: r-help at r-project.org
> Subject: [R] Contradictory results between different heteroskedasticity
> tests
> 
> Hi all,
> 
> I'm getting contradictory results from bptest and ncvTest on a model
> calculated by GLS as:
> 
> olslm = lm(log(rr)~log(aloi)*reg*inv, data)
> varlm = lm(I(residuals(olslm)^2)~log(aloi)*reg*inv, data)
> glslm = lm(log(rr)~log(aloi)*reg*inv, data, weights=1/fitted(varlm))
> 
> Testing both olslm and glslm with both ncvTest and bptest gives:
> 
> > ncvTest(olslm)
> Non-constant Variance Score Test
> Variance formula: ~ fitted.values
> Chisquare = 46.88206    Df = 1     p = 7.538963e-12
> 
> > ncvTest(glslm)
> Non-constant Variance Score Test
> Variance formula: ~ fitted.values
> Chisquare = 0.001466426    Df = 1     p = 0.9694533
> 
> > bptest(olslm)
>         studentized Breusch-Pagan test
> data:  olslm
> BP = 213.1477, df = 7, p-value < 2.2e-16
> 
> > bptest(glslm)
>         studentized Breusch-Pagan test
> data:  glslm
> BP = 213.1477, df = 7, p-value < 2.2e-16
> 
> Please notice the last output. It seems as if bptest is not
> considering the weights given to lm. What am I doing wrong here?
> 
> Best regards
> --
> Carlos
> 
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