similar to: Stepwise in lme

Displaying 20 results from an estimated 5000 matches similar to: "Stepwise in lme"

2010 Aug 17
2
how to selection model by BIC
Hi All: the package "MuMIn" can be used to select the model based on AIC or AICc. The code is as follows: data(Cement) lm1 <- lm(y ~ ., data = Cement) dd <- dredge(lm1,rank="AIC") print(dd) If I want to select the model by BIC, what code do I need to use? And when to select the best model based on AIC, what the differences between the function "dredge" in
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]]
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
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
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.
2003 Jun 20
2
stepwise regression
Hi, S-PLUS includes the function "stepwise" which can use a variety of methods to conduct stepwise multiple linear regression on a set of predictors. Does a similar function exist in R? I'm having difficulty finding one. If there is one it must be under a different name because I get an error message when I try 'help(stepwise)' in R. Thanks for your help, Andy Taylor
2006 Jun 14
3
A question about stepwise procedures: step function
Dear all, I tried to use "step" function to do model selection, but I got an error massage. What I don't understand is that data as data.frame worked well for my other programs, how come I cannot make it run this time. Could you please tell me how I can fix it? ***************************************************************************************************
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
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
2011 Nov 04
2
Select some, but not all, variables stepwise
Hi, I would like to fit a linear model where some but not all explanators are chosen stepwise - ie I definitely want to include some terms, but others only if they are deemed significant (by AIC or whatever other approach is available). For example if I wanted to definitely include x1 and x2, but only include z1 and z2 if they are significant, something like this: df <-
2012 Feb 17
3
stepwise selection for conditional logistic regression
 Hi, Is there any function available to do stepwise selection of variables in Conditional(matched) logistic regression( clogit)? step, stepwise  etc are failing in case of conditional logistic regression. Please help.  Thanks P.T. Subha [[alternative HTML version deleted]]
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
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
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
2012 Apr 09
1
Stepwise procedure with force.in command
Dear R-helpers, I am trying to do a stepwise procedure in which I want to force some variables in the model. I have searched around and it seems that only leaps package allows to force the variable in the stepwise procedure. I use the leaps package and use the regsubsets(lm1, force.in = 1, data) to force 1 variable in the model. However, the force.in command only allow me to force 1 variable
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,
2001 Nov 05
1
stepwise algorithm step() on coxph() (PR#1159)
Full_Name: Jerome Asselin Version: 1.3.1 OS: MacOS 9.2 Submission from: (NULL) (142.103.173.46) The step() function attempts to calculate the deviance of fitted models even if does not really need it. As a consequence, the step() function gives an error when it is used with coxph(). (There is currently no method to calculate the deviance of coxph() fits.) The code below gives an example of how
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
2012 Nov 19
9
Stepwise analysis with fixed variables
Hello, How can I run a backward stepwise regression with part of the variables fixed, while the others participate in the backward stepwise analysis? Thank you, Einat -- View this message in context: http://r.789695.n4.nabble.com/Stepwise-analysis-with-fixed-variables-tp4650015.html Sent from the R help mailing list archive at Nabble.com.