Displaying 20 results from an estimated 500 matches similar to: "summary(lm ... conrasts=...)"
2009 Nov 08
2
reference on contr.helmert and typo on its help page.
I'm wondering which textbook discussed the various contrast matrices
mentioned in the help page of 'contr.helmert'. Could somebody let me
know?
BTW, in R version 2.9.1, there is a typo on the help page of
'contr.helmert' ('cont.helmert' should be 'contr.helmert').
2004 Mar 03
1
Confusion about coxph and Helmert contrasts
Hi,
perhaps this is a stupid question, but i need some help about
Helmert contrasts in the Cox model.
I have a survival data frame with an unordered factor `group'
with levels 0 ... 5.
Calculating the Cox model with Helmert contrasts, i expected that
the first coefficient would be the same as if i had used treatment
contrasts, but this is not true.
I this a error in reasoning, or is it
2005 Apr 13
2
multinom and contrasts
Hi,
I found that using different contrasts (e.g.
contr.helmert vs. contr.treatment) will generate
different fitted probabilities from multinomial
logistic regression using multinom(); while the fitted
probabilities from binary logistic regression seem to
be the same. Why is that? and for multinomial logisitc
regression, what contrast should be used? I guess it's
helmert?
here is an example
2001 Jun 15
1
contrasts in lm and lme
I am using RW 1.2.3. on an IBM PC 300GL.
Using the data bp.dat which accompanies
Helen Brown and Robin Prescott
1999 Applied Mixed Models in Medicine. Statistics in Practice.
John Wiley & Sons, Inc., New York, NY, USA
which is also found at www.med.ed.ac.uk/phs/mixed. The data file was opened
and initialized with
> dat <- read.table("bp.dat")
>
2005 Jun 23
4
contrats hardcoded in aov()?
On 6/23/05, RenE J.V. Bertin <rjvbertin at gmail.com> wrote:
> Hello,
>
> I was just having a look at the aov function source code, and see that when the model used does not have an Error term, Helmert contrasts are imposed:
>
> if (is.null(indError)) {
> ...
> }
> else {
> opcons <- options("contrasts")
>
2006 Sep 29
1
Helmert contrasts for repeated measures and split-plot expts
Dear R-help
I have two separate experiments, one a repeated-measures design, the other
a split-plot. In a standard ANOVA I have usually undertaken a
multiple-comparison test on a significant factor with e.g TukeyHSD, but as
I understand it such a test is inappropriate for repeated measures or
split-plot designs.
Is it therefore sensible to use Helmert contrasts for either of these
designs?
2005 Apr 23
2
ANOVA with both discreet and continuous variable
Hi all,
I have dataset with 2 independent variable, one (x1)
is continuous, the other (x2) is a categorical
variable with 2 levels. The dependent variable (y) is
continuous. When I run linear regression y~x1*x2, I
found that the p value for the continuous independent
variable x1 changes when different contrasts was used
(helmert vs. treatment), while the p values for the
categorical x2 and
2013 Feb 11
2
stringsAsFactors
I think your idea to remove the warnings is excellent, and a good compromise. Characters
already work fine in modeling functions except for the silly warning.
It is interesting how often the defaults for a program reflect the data sets in use at the
time the defaults were chosen. There are some such in my own survival package whose
proper value is no longer as "obvious" as it was
2000 Aug 01
1
Testing for parallel slopes
I'm running a series of simple bivariate linear regressions on grouped
data. I want to test the slopes to see if they are parallel. I normally
use analysis of covariance to do so, looking at interaction between the
covariate and the factor to make this determination.
VR3 pp.149 - 154 has a very nice example of an ANOCOVA, ending with a
discussion of this very operation.
My question has
2007 Oct 11
2
Type III sum of squares and appropriate contrasts
I am running a two-way anova with Type III sums of squares and would
like to be able to understand what the different SS mean when I use
different contrasts, e.g. treatment contrasts vs helmert contrasts. I
have read John Fox's "An R and S-Plus Companion to Applied Regression"
approach -p. 140- suggesting that treatment contrasts do not usually
result in meaningful results with Type
2008 Sep 26
1
Type I and Type III SS in anova
Hi all,
I have been trying to calculate Type III SS in R for an unbalanced two-way
anova. However, the Type III SS are lower for the first factor compared to
type I but higher for the second factor (see below). I have the impression
that Type III are always lower than Type I - is that right?
And a clarification about how to fit Type III SS. Fitting model<-aov(y~a*b)
in the base package and
2006 Jun 14
2
lmer binomial model overestimating data?
Hi folks,
Warning: I don't know if the result I am getting makes sense, so this
may be a statistics question.
The fitted values from my binomial lmer mixed model seem to
consistently overestimate the cell means, and I don't know why. I
assume I am doing something stupid.
Below I include code, and a binary image of the data is available at
this link:
2009 Mar 06
1
Interpreting GLM coefficients
Hi all,
I?m fitting GLM?s and I can?t interprete the coefficients when I run a
model with interaction terms.
When I run the simpliest model there is no problem:
Model1<-glm (Fishes ~ Year + I(Year^2) + Kind.Geographic +
Kind.Fishers + Zone.2 + Hours + Fishers + Month, family =
poisson(log)) # Fishes, Year, Hours, and Fishers are numeric,
Kind.Geographic, Kind.Fishers, Zone.2 and
2003 Aug 14
1
gnls - Step halving....
Hi all,
I'm working with a dataset from 10 treatments, each
treatment with 30 subjects, each subject measured 5
times. The plot of the dataset suggests that a
3-parameter logistic could be a reasonable function to
describe the data. When I try to fit the model using
gnls I got the message 'Step halving factor reduced
below minimum in NLS step'. I´m using as the initial
values of the
2006 Apr 19
1
Can't run code from "Mixed Effects Models in S and S-plus"
Dear R-users:
I can't run the following code from "Mixed Effects Models in S and S-plus".
library( nlme )
options( width = 65, digits = 5 )
options( contrasts = c(unordered = "contr.helmert", ordered = "contr.poly")
)
# Chapter 5 Extending the Basic Linear Mixed-Effects Models
# 5.1 General Formulation of the Extended Model
data( Orthodont )
vf1Fixed
2005 Feb 23
1
model.matrix for a factor effect with no intercept
I was surprised by this (in R 2.0.1):
> a <- ordered(-1:1)
> a
[1] -1 0 1
Levels: -1 < 0 < 1
> model.matrix(~ a)
(Intercept) a.L a.Q
1 1 -7.071068e-01 0.4082483
2 1 -9.073800e-17 -0.8164966
3 1 7.071068e-01 0.4082483
attr(,"assign")
[1] 0 1 1
attr(,"contrasts")
attr(,"contrasts")$a
[1]
2005 Nov 24
2
type III sums of squares in R
Hi everyone,
Can someone explain me how to calculate SAS type III sums of squares in
R? Not that I would like to use them, I know they are problematic. I
would like to know how to calculate them in order to demonstrate that
strange things happen when you use them (for a course for example). I
know you can use drop1(lm(), test="F") but for an lm(y~A+B+A:B), type
III SSQs are only
2011 May 21
2
unbalanced anova with subsampling (Type III SS)
Hello R-users,
I am trying to obtain Type III SS for an ANOVA with subsampling. My design
is slightly unbalanced with either 3 or 4 subsamples per replicate.
The basic aov model would be:
fit <- aov(y~x+Error(subsample))
But this gives Type I SS and not Type III.
But, using the drop() option:
drop1(fit, test="F")
I get an error message:
"Error in
2005 May 20
1
Problem with proj
Hi all,
Perhaps this in an inappropriate post, but I've found a bug in proj
I'd like to track down a bit further before making a formal bug report.
The example below shows the problem, if you change the rownames proj
fails. The problem seems to be that there is a mismatch in the rownames
in the qr objects constructed by aov and the rownames that proj is
expecting them to have.
2008 Nov 14
1
aov help
Please pardon an extremely naive question. I see related earlier
posts, but no responses which answer my particular question. In
general, I'm very confused about how to do variance decomposition with
random and mixed effects. Pointers to good tutorials or texts would
be greatly appreciated.
To give a specific example, page 193 of V&R, 3d Edition, illustrates
using raov assuming pure