similar to: Handle lot of variables - Regression

I have some data 'myData' in wide form (attached at the end), and would like to convert it to long form. I wish to have five variables in the result: 1) Subj: factor 2) Group: between-subjects factor (2 levels: s / w) 3) Reference: within-subject factor (2 levels: Me / She) 4) F: within-subject factor (2 levels: F1 / F2) 5) J: within-subject factor (2 levels: J1 / J2) As this is the

Hi, I am trying to read the "credit.lisp" file of the Japanese credit database in UCI repository, but it is in lisp format which I do not know how to read. I have not found how to do that in the foreign library http://archive.ics.uci.edu/ml/datasets/Japanese+Credit+Screening <http://archive.ics.uci.edu/ml/datasets/Japanese+Credit+Screening> Could anyone help me? Best

On Debian the Asterisk Makefile does /usr/sbin/update-rc.d asterisk start 10 2 3 4 5 . stop 91 2 3 4 5 .; which results in a /etc/rc2.d/S10asterisk being written. I think S10 is too early. bind9 : S15 mysql : S19 zaptel: S20 ntp : S23 What bothers me most is that mysql is not up when asterisk starts. That's a bad thing if there are #execs in your config files and if the scripts rely on

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

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

Hi everyone, I am wondering if there exists a stepwise regression function for the Bayesian regression model. I tried googling, but I couldn't find anything. I know "step" function exists for regular stepwise regression, but nothing for Bayes. Thanks -- View this message in context: http://www.nabble.com/Bayesian-regression-stepwise-function--tp26013725p26013725.html Sent from

Dear Gurus, Thank you in advance for your assistance. I'm trying to understand scope better when performing stepwise regression using "step." I have a model with a binary response variable and 10 predictor variables. When I perform stepwise regression I define scope=.^2 to allow interactions between all terms. But I am missing something. When I perform stepwise regression (both

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

 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]]

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.

Sorry, I have wrote a wrong subject in the first email! Regards, Linda ---------- Forwarded message ---------- From: linda Porz <linda.porz@gmail.com> Date: 2011/5/25 Subject: combined odds ratio To: r-help@r-project.org Cc: r-help-request@stat.math.ethz.ch Dear all, I am looking for an R function which does stepwise selection cox model in r (delta chisq likelihood ratio test) similar

I use the step() function occasionally, and I think I understand its objective, proper use, and limitations. Now I see stepwise model selection being used in what seems to be an unusual way, and I wonder if it is right or wrong. May I describe? Genetic mapping tries to find where in an animal's genome are genetic elements that influence a particular physical trait. Say there are 100

Hello, I have been using the step() function for stepwise regression and was wondering if there was a way to specify a tolerance level either using step() or another stepwise function. So far I have only found an option to specify tolerance in lm.fit() but I am not an experienced R user and am not quite sure if this command can be implemented using a stepwise function. I have tried simply

Hi, I know that is not possible make a stepwise procedure using REML in R, I can use ML for this. For nested design it may be very dangerous due the difference in variance structure, mainly in a splitplot design. ML make significative variables that REML dont make. I read an article that is made a stepwise procedure using GENSTAT. from article: "Terms were dropped from a model in a

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 <-

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]]

Dear all, I am wondering why the step() procedure in R has the description 'Select a formula-based model by AIC'. I have been using Stata and SPSS and neither package made any reference to AIC in its stepwise procedure, and I read from an earlier R-Help post that step() is really the 'usual' way for doing stepwise (R Help post from Prof Ripley, Fri, 2 Apr 1999 05:06:03

Dear all, I have data.frame object in R. I want to export it in tab-delimited file with several lines of header initiated with comment sign (#). I do not know how to do that in R. Could you please give helps on this problem? Thanks in advance. Best, Jian-Feng, ################################################################## The lines I want to write in the header lines look like, with words

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

Dear All, Probably it is not highly relevant question: Why do stepwise regression functions in R (step() or stepAIC()) add/delete categorical variables as a set? For example, I have a four-level factor variable d, so dummies are d1,d2,d3, as stepwise regression operates d, adding or removing, d1,d2,d3 are simultaneously added/removed. What's the concern here if operating dummies individually?