similar to: Logistic Regression

I am creating habitat selection models for caribou and other species with data collected from GPS collars. In my current situation the radio-collars recorded the locations of 30 caribou every 6 hours. I am then comparing resources used at caribou locations to random locations using logistic regression (standard habitat analysis). The data is therefore highly autocorrelated and this causes Type

I would like to perform a bootstrap validation of a backward stepwise logistic regression analysis, but I am a beginner with R and I am not sure of how to do it. Is there anyone that can send me a sample file in tab format (that I can modify in Excel by pasting my data) and the pertinent R algorithm? Many thanks Giuseppe -- ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Dr. Giuseppe Biondi

I was unsure of what suitable goodness-of-fit tests existed in R for logistic regression. After searching the R-help archive I found that using the Design models and resid, could be used to calculate this as follows: d <- datadist(mydataframe) options(datadist = 'd') fit <- lrm(response ~ predictor1 + predictor2..., data=mydataframe, x =T, y=T) resid(fit, 'gof'). I set up a

I am using GLM to calculate logit models based on cross-sectional data. I am now down to the hard work of making the results intelligible to very average readers. Is there any way to calculate a psuedo analoque to the R^2 in standard linear regression for use as a purely descriptive statistic of goodness of fit? Most of the readers of my report will be vaguely familiar and more comfortable with

 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]]

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

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Hi, it seems that the fastbw() in the Design package only works with variable of class "factor" according to the help page if I understand correctly. Is there any R function/package that do stepwise variable selection for a Cox model with continuous independent variables? Thank you John ____________________________________________________________________________________ Looking

Hello useRs, I have a problem at hand which I'd think is fairly common amongst groups were R is being adopted for Analytics in place of SAS. Users would like to obtain results for logistic regression in R that they have become accustomed to in SAS. Towards this end, I was able to propose the Design package in R which contains many functions to extract the various metrics that SAS reports.

Hi All, I know in R there is function named 'step', which does the stepwise regression and choose the model by AIC. However, if I want to choose a model per this logic: 1. Run a full model (linear regression, f = lm(y ~., data = ZZZ), for example) 2. Pick up the variable with biggest p value, delete it from the module and get a new regression model. 3. Repeat step 2

Hi all, I am trying to fit a logistic regression for a bivariate response using five independent variables in a stepwise procedure. My outputs look okay but does any one know (or is there any literature on) how the confidence intervals are calculated for the reported odds ratios..? Thanks! [[alternative HTML version deleted]]

Hi, R users, What may be the best function in R to do variable selection in logistic regression? I have the same number of variables as the number of samples, and I want to select the best variablesfor prediction. Is there any function doing forward selection followed by backward elimination in stepwise logistic regression? Thanks, Annie [[alternative HTML version deleted]]

Dear R-help members, I'd like to run a binomial logistic stepwise regression with ten explanatory variables and as many interaction terms as R can handle. I'll come up with the right R command sooner or later, but my real question is whether and how the criterion for the evaluation of the different models can be set to be the probability of the residual deviance in the Chi-Square

Hello, Does logistic regression really provide better results than lda or qda ? (my purpose is not classification but highlighting of discriminant variables). If this is true, where could I get an R script performing stepwise logistic regression ? Thanks -- Daniel AMORESE Lab. M2C "Morphodynamique Continentale et C?ti?re" UMR CNRS 6143 Caen/Rouen Centre de G?omorphologie UCBN

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.

Hi all, I am running Stepwise logistic regression and i have : 1- Multiple covatiates included in each model (No missing data) 2- Genotype data (SNPs) about 500,000 . I partitioned the data to multiple files (there are missing data) I run the step by including all the covariates and one SNP at each model. but i got this message : number of rows in use has changed: remove missing values? In

Dear All, For logistic regression models: is it possible to use validate (rms package) to compute bias-corrected AUC, but have variable selection with AIC use step (or stepAIC, from MASS), instead of fastbw? More details: I've been using the validate function (in the rms package, by Frank Harrell) to obtain, among other things, bootstrap bias-corrected estimates of the AUC, when variable

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.

Hi, I was wondering whether this query was addressed on how to perform validation through boostrapping. I am currently trying to implement a boostrapping approach to validation but don't know where to start. Help please. Thank you and Regards, Vivienne Ozohili Risk Model Validation Manager Group Risk Independent Control Unit A5, Bank of Ireland Head Office Lower Baggot Street Dublin 2 Tel:

(PLS, also CC: to 7ukwn@wanadoo.fr, which is my private address) Hi, I'm trying to setup 2 boxes with Asterisk; one with one quicknet PhoneCard, the other with two Quicknet cards: a PhoneCard and a LineJack; either boxes have a phone connected to the PhoneCards, a regular line is connected to the LineJack They'll be both on the internet (by adsl) and the purpose is to be able to make