Thank you very much, John. This has allowed us to move forward on several
fronts and better understand our data.
- Michael Cohn
On Tue, Sep 26, 2023 at 8:39 AM John Fox wrote:
> Dear Michael,
>
> My previous response was inaccurate: First, linearHypothesis() *is* able
> to accommodate aliased c
Dear Michael,
My previous response was inaccurate: First, linearHypothesis() *is* able
to accommodate aliased coefficients by setting the argument singular.ok
= TRUE:
> linearHypothesis(minimal_model, "bt2 + csent + bt2:csent = 0",
+ singular.ok=TRUE)
Linear hypothesis test:
Dear Michael,
You're testing a linear hypothesis, so there's no need to use the delta
method, but the linearHypothesis() function in the car package also
fails in your case:
> linearHypothesis(minimal_model, "bt2 + csent + bt2:csent = 0")
Error in linearHypothesis.lm(minimal_model, "bt2 + cse
I'm running a linear regression with two categorical predictors and their
interaction. One combination of levels does not occur in the data, and as
expected, no parameter is estimated for it. I now want to significance test
a particular combination of levels that does occur in the data (ie, I want
Rseek.org brings up what look like relevant hits on "conditional
autoregressive models." Have you looked at these? If so and they do
not suit, perhaps you should explain why not. If they do, please do
such searching on your own in future.
Cheers,
Bert
Bert Gunter
"The trouble with having an ope
*I would like to simulate spatial data conditional **autoregressive
(CAR) model with weighted matrix order 2**Is there any package or
function in R to perform it ?
**Thanks in advance*
*Best Regards
Siswanto*
--
*Siswanto*
Department of Statistics, Faculty of Mathematics and Natural Science
Bogo
Dear Phil,
I'll bypass questions about why one would want to do this, why you're using
glm() rather than lm(), etc., and just point out that the *studentized*
residual for the 11th observation is undefined for your example. Simplifying
your code:
snip ---
> y <- c(1.00,1.00,1.00,
Hi all,
as John pointed out, there is a way to create settings where the
studentized residuals are undefined. However, after cross-checking it
seems that the residuals are getting calculated without any error. The
problem comes up when I use outlierTest to assign a p,q value,respectively.
Be
Dear Phil,
Yes, that's a bit clearer. One can invent data configurations where certain
studentized residuals are undefined. For example, try the following:
y <- c(0, 0, 0, 0, 0, 1)
x <- 1:6
xx <- (1:6 - 3.5)^2
rstudent(lm(y ~ x))
rstudent(lm(y ~ xx))
plot(x, y)
plot(xx, y)
The plots should clar
Dear Phil,
After reading your posting several times, I still don't understand what you
did. As usual, having a reproducible example illustrating the error would be a
great help. I do have a guess about the source of the error: glm() failed in
some way for the problematic case.
Best,
John
---
Hi guys,
I came across a strange phenomena and can't figure out why it happens by
myself so here we go.
I got a dataframe which consists of double numbers which I want to
check, row-wise if there are outliers in the rows.
So I iterate over the rows and create a glm using the numbers of that
: Tuesday, October 09, 2012 4:00 PM
To: John Jay Wiley Jr.
Cc: r-help@r-project.org
Subject: RE: [R] car::linearHypothesis Sum of Sqaures Error?
Dear John,
> -Original Message-
> From: John Jay Wiley Jr. [mailto:jwile...@syr.edu]
> Sent: Tuesday, October 09, 2012 3:37 PM
> To: J
Dear John,
> -Original Message-
> From: John Jay Wiley Jr. [mailto:jwile...@syr.edu]
> Sent: Tuesday, October 09, 2012 3:37 PM
> To: John Fox
> Cc: r-help@r-project.org
> Subject: RE: [R] car::linearHypothesis Sum of Sqaures Error?
>
> John,
>
> A
variances are similar. Is there
another metric I am missing for a continuous covariate?
Cheers,
John
From: John Fox [j...@mcmaster.ca]
Sent: Tuesday, October 09, 2012 2:59 PM
To: John Jay Wiley Jr.
Cc: r-help@r-project.org
Subject: RE: [R] car::linearHypo
Dear John,
> -Original Message-
> From: John Jay Wiley Jr. [mailto:jwile...@syr.edu]
> Sent: Tuesday, October 09, 2012 9:17 AM
> To: John Fox
> Cc: r-help@r-project.org
> Subject: RE: [R] car::linearHypothesis Sum of Sqaures Error?
>
> John,
>
> Thank yo
l and Forest Biology
460 Illick Hall
Syracuse, NY 13210
315.470.4825 (office)
740.590.6121 (cell)
From: John Fox [j...@mcmaster.ca]
Sent: Tuesday, October 09, 2012 7:15 AM
To: John Jay Wiley Jr.
Cc: r-help@r-project.org
Subject: Re: [R] car::linearHypothe
Dear John
On Tue, 9 Oct 2012 02:07:07 +
"John Jay Wiley Jr." wrote:
> I am working with a RCB 2x2x3 ANCOVA, and I have noticed a difference in the
> calculation of sum of squares in a Type III calculation.
For type III tests, you should use contrasts that are orthogonal in the row
basis o
I am working with a RCB 2x2x3 ANCOVA, and I have noticed a difference in the
calculation of sum of squares in a Type III calculation.
Anova output is a follows:
> Anova(aov(MSOIL~Forest+Burn*Thin*Moisture+ROCK,data=env3l),type=3)
Anova Table (Type III tests)
Response: MSOIL
Pr(>F)
1 45 322.54
2 44 311.97 110.567 1.4903 0.2287
Best,
John
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Iuri Gavronski
> Sent: August-15-12 4:47 AM
> To: r-help
>
Hi,
I am trying to test whether a factor (coded as a set of dummy
variables) is equal to zero, using linearHypothesis. I get an error.
See a reproducible example:
data(swiss)
my_swiss = swiss
my_swiss$fake = factor(sample(c("A","B"),47,rep=T))
my_lm <- lm(Infant.Mortality ~ Fertility + fake, data
On Jul 23, 2012, at 02:48 , John Fox wrote:
[snip long discussion which I admit not to have studied in every detail...]
>>
>> Unfortunately, my involvement with this issue has led me to another
>> question. Winer and Kirk both discuss a split-plot ANCOVA in which one has
>> measured a covaria
F value Pr(>F)
> >> (Intercept) 3.01 11.40 0.264
> >> treatment 13.71 23.18 0.085 .
> >> age11.56 15.37 0.043 *
> >> treatment:age 13.37 23.11 0.089 .
> >> Residuals 21.53 10
> >> ---
> >&g
s
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox
-----Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Henrik Singmann
Sent: July-21-12 1:29 PM
To: r-h...@stat.math.ethz.ch
Subject: [R]
m not sure why
> > you would want to do so, but you could simply ignore these tests.
> >
> > I hope this helps,
> > John
> >
> >
> > John Fox
> > Senator William McMaster
> >Professor of Social Statistics
&
-
project.org] On Behalf Of Henrik Singmann
Sent: July-21-12 1:29 PM
To: r-h...@stat.math.ethz.ch
Subject: [R] car::Anova - Can it be used for ANCOVA with repeated-
measures factors.
Dear list,
I would like to run an ANCOVA using car::Anova with repeated measures
factors, but I can't figure
..@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Henrik Singmann
> Sent: July-21-12 1:29 PM
> To: r-h...@stat.math.ethz.ch
> Subject: [R] car::Anova - Can it be used for ANCOVA with repeated-
> measures factors.
>
> Dear list,
>
> I would like to r
Dear list,
I would like to run an ANCOVA using car::Anova with repeated measures factors,
but I can't figure out how to do it. My (between-subjects) covariate always
interacts with my within-subject factors.
As far as I understand ANCOVA, covariates usually do not interact with the
effects of
Dear Ranjan,
As you no doubt noticed, the Manova() function in the car package, or the
Anova() function for which Manova() is an alias, produces type II or III tests
for a multivariate linear model. To compare two nested multivariate linear
models, as you wish to do, you can use the standard R
Dear colleagues,
I had a question wrt the car package. How do I evaluate whether a
simpler multivariate regression model is adequate?
For instance, I do the following:
ami <- read.table(file =
"http://www.public.iastate.edu/~maitra/stat501/datasets/amitriptyline.dat";,
col.names=c("TCAD", "drug"
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