Displaying 20 results from an estimated 10000 matches similar to: "Robust Stepwise Regression"
2003 May 08
2
Forward Stepwise regression with stepAIC and step
Dear all,
I cannot seem to get the R functions step or stepAIC to perform forward
or stepwise regression as I expect. I have enclosed the example data in
a dataframe at the end of this mail. Note rubbish is and rnorm(17) variable
which I have deliberately added to the data to test the stepwise procedure.
I have used
wateruse.lm<-lm(waterusage~.,data=wateruse) # Fit full model
2005 Dec 08
1
mle.stepwise versus step/stepAIC
Hello,
I have a question pertaining to the stepwise regression which I am trying to
perform. I have a data set in which I have 14 predictor variables
accompanying my response variable. I am not sure what the difference is
between the function "mle.stepwise" found in the wle package and the
functions "step" or "stepAIC"? When would one use
2003 Jun 18
2
Forward stepwise procedure w/ stepAIC
I'm attempting to select a model using stepAIC. I want to use a forward
selection procedure. I have specified a "scope" option, but must not be
understanding how this works. My results indicate that the procedure begins
and ends with the "full" model (i.e., all 17 independent variables)...not
what I expected. Could someone please point out what I'm not
2010 Apr 13
1
stepwise regression-fitting all possible models
Dear All,
I am new to R and I would like to do the following:
I want to fit a logistic model with 3 predictors and then perform a stepwise
regression to select the best possible model using either the AIC/BIC
criterion.
I have used the stepAIC function which works fine but using this method only
likely candidates are evaluated (i.e. not all the models are fitted). We
should have 2^3=8 possible
2008 Oct 22
1
forward stepwise regression using Mallows Cp
So I recognize that:
1. many people hate forward stepwise regression (i've read the archives)--but I need it
2. step() or stepAIC are two ways to get a stepwise regression in R
But here's the thing: I can't seem to figure out how to specify that I want the criteria to be Mallow's Cp (and then to subsequently tell me what the Cp stat is). I know it has something to do with
2005 Feb 25
0
Bayesian stepwise (was: Forward Stepwise regression based onpartial F test)
oops,
Forgot to cc to the list.
Regards,
Mike
-----Original Message-----
From: dr mike [mailto:dr.mike at ntlworld.com]
Sent: 24 February 2005 19:21
To: 'Spencer Graves'
Subject: RE: [R] Bayesian stepwise (was: Forward Stepwise regression based
onpartial F test)
Spencer,
Obviously the problem is one of supersaturation. In view of that, are you
aware of the following?
A Two-Stage
2008 May 09
2
Stepwise regression
I am using stepAIC for stepwise regression modeling.
Is there a way to change the entry and exit alpha levels for the
stepwise regression using stepAIC ?
Many thanks,
Berthold
Berthold Stegemann
Bakken Research Center
Maastricht
The Netherlands
[[alternative HTML version deleted]]
2011 Dec 22
2
Stepwise in lme
I'm manually doing a form of stepwise regression in a mixed model but with
many variables, it is time consuming. I thought I'd try to use an automated
approach. stepAIC gave me false convergence when I used it with my model,
so I thought it can't be hard to set up a basic program to do it based on
the p-values. Thus I tried a couple of (very) crude options:
1) trying to
2009 May 05
2
Stepwise logistic Regression with significance testing - stepAIC
Hello R-Users,
I have one binary dependent variable and a set of independent variables (glm(formula,…,family=”binomial”) ) and I am using the function stepAIC (“MASS”) for choosing an optimal model. However I am not sure if stepAIC considers significance properties like Likelihood ratio test and Wald test (see example below).
> y <- rbinom(30,1,0.4)
> x1 <- rnorm(30)
> x2
2006 Apr 28
4
stepwise regression
Dear all,
I have encountered a problem when perform stepwise regression.
The dataset have more 9 independent variables, but 7 observation.
In R, before performing stepwise, a lm object should be given.
fm <- lm(y ~ X1 + X2 + X3 + X11 + X22 + X33 + X12 + X13 + X23)
However, summary(fm) will give:
Residual standard error: NaN on 0 degrees of freedom
Multiple R-Squared: 1, Adjusted
2005 Oct 25
0
One more about Error in step() (or stepAIC) for Cox model
Thank you for Prof.Ripley's suggestion. I fixed the program by adding a
lower scope, and the program ran, but I still got warning messages, and
don't know what is going on, would this affect my results?
...
Step: AIC= 12337.74
Surv(tlfup, cen) ~ MI[[j]]$trt + MI[[j]]$agem40 + MI[[j]]$agem40sq +
mhtypeed1 + mhtypeed2
Df AIC
<none> 12338
-
2000 Jan 04
0
Stepwise logistic discrimination - II
I apologise for writing again about the problem with using stepAIC +
multinom, but I think the reason why I had it in the first place is
perhaps there may be a bug in either stepAIC or multinom.
Just to repeat the problem, I have 126 variables and 99 cases. I don't
know if the large number of variables could be the problem. Of couse the
reason for doing a stepwise method is to reduce this
2012 Sep 19
0
Lowest AIC after stepAIC can be lowered by manual reduction of variables (Florian Moser)
A few general comments about stepwiseAIC and a suggestion of how to select models
a) Apart form the problem, that stepwise selection is not a garanty to get the best model, you need to have a lot of data to avoid overfitting if your model includes 7 parameter plus interactions (> 10 observations per parameter is what you are ideally looking for).
b) Have a look at Anderson and Burnham's
2003 Sep 30
1
Stepwise procedures
Is there a function in R which performs stepwise estimation in ways similar
to SAS/STATA (i.e., allows the analyst to specify the significance levels
for removal/addition of terms).
I've been asked to evaluate two final models: one resulting from a
backwards selection in R (stepAIC) and one resulting from a backwards
selection using PROC LOGISTIC in SAS. The final terms are slightly
2007 Sep 17
1
Stepwise logistic model selection using Cp and BIC criteria
Hi,
Is there any package for logistic model selection using BIC and Mallow's Cp
statistic? If not, then kindly suggest me some ways to deal with these
problems.
Thanks.
--
View this message in context: http://www.nabble.com/Stepwise-logistic-model-selection-using-Cp-and-BIC-criteria-tf4464430.html#a12729613
Sent from the R help mailing list archive at Nabble.com.
2012 Sep 18
1
Lowest AIC after stepAIC can be lowered by manual reduction of variables
Hello
I am not really a statistic person, so it's possible i did something completely wrong... if this is the case: sorry...
I try to get the best GLM model (with the lowest AIC) for my dataset.
Therefore I run a stepAIC (in the "MASS" package) for my GLM allowing only two-variable-interactions.
For the output (summary) I got a model with 7 (of 8) variabels and 5 interactions and
2005 Oct 24
1
Error in step() (or stepAIC) for Cox model
Hello all,
I am trying to use stepwise procedure to select covariates in Cox model
and use bootstrap to repeat stepwise selection, then record how many
times variables are chosen by step() in bootstrap replications. When I
use step() (or stepAIC) to do model selection, I got errors. Here is the
part of my code
for (j in 1:mm){ #<--mm=10
for (b in 1:nrow(reg.bs)){ #<--bootstrap 10
2005 Feb 24
2
Forward Stepwise regression based on partial F test
I am hoping to get some advise on the following:
I am looking for an automatic variable selection procedure to reduce the
number of potential predictor variables (~ 50) in a multiple regression
model.
I would be interested to use the forward stepwise regression using the
partial F test.
I have looked into possible R-functions but could not find this
particular approach.
There is a function
2010 Sep 02
1
Is there any package or function perform stepwise variable selection under GEE method?
Hi ,
I use library(gee),library(geepack),library(yags) perform GEE data analysis
, but all of them cannot do variable selection!
Both step and stepAIC can do variable selection based on AIC criterion under
linear regression and glm,
but they cannot work when model is based on GEE.
I want to ask whether any variable selection function or package under GEE
model avaliable now?
Thanks!
Best,
2007 Nov 15
0
Package to make stepwise model selection using F or Chisq test
Hi,
I looking for a method that use F or Chisq test instead of AIC in a stepwise
modelo selection.
I try the grasp package using the grasp.step.anova, but It dont work.
> library(grasp)
Carregando pacotes exigidos: gam
Carregando pacotes exigidos: splines
Carregando pacotes exigidos: mda
Carregando pacotes exigidos: class
> data(anorexia,package="MASS")
>
> m1 <-