similar to: a question regarding 'lrm'

Hi all, I try to test a linear slope using offset. I have: > m2 <- glm(Y~X*V) > summary(m2) Call: glm(formula = Y ~ X * V) Deviance Residuals: Min 1Q Median 3Q Max -2.01688 -0.56028 0.05224 0.53213 3.60216 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.3673 0.8476 1.613 0.119788 X

Hello. I am still a newbie in R. Excuse me if I am asking something obvious. My efforts to get an answer through browsing the mailing archives failed. I want to perform an augmented Dickey-Fuller test and to obtain AIC and BIC and to be able to impose some linear restrictions on the ADF regression so as to decide the correct order of autoregression. However I could find no obvious way to impose

Hello, I have a question on unit root test with urca toolbox. First, to run a unit root test with lags selected by BIC, I type: > CPILD4UR<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags=12, selectlags ="BIC") > summary(CPILD4UR) The results indicate that the optimal lags selected by BIC is 4. Then I run the same unit root test with drift and 4 lags:

Dear R-helpeRs, I was not sure if this is ESS-specific or Mac-specific etc, so I send in the main list. I had the setup emacs+ess+R 2.2.1 running fine (on a powerbook G4). I recently upgraded R to 2.3.0 and it runs fine from the GUI and from the terminal. However, when I try to run it from emacs (which was running fine with R2.2.1) I get the "Process R is not running" message.

Works correctly for me in the Rtools directory on 2.3.1. Any more clues as to how to reproduce this? On Wed, 6 Sep 2006, Johannes.Prix at wu-wien.ac.at wrote: > Full_Name: Johannes Prix > Version: 2.3.1/2.3.0 not 2.1.1 > OS: Windows XP Service Pack 2 Build 2600.xpsp_sp2_gdr.0503011519 > Submission from: (NULL) (137.208.41.103) > > > > In a vanilla R, version 2.3.1 or

Hi, I've got the following two versions of R on WinXP: A) R Version 2.3.0 Under development (unstable) (2006-02-02 r37243) B) R Version 2.3.0 Under development (unstable) (2006-03-27 r37579) and a the following "test.R" script: foo <- function(path, ...) { print(path) } bar <- function(x, ...) foo(...) wow <- function(x, ...) capture.output(foo(...)) bar(1, path=2)

Full_Name: Johannes Prix Version: 2.3.1/2.3.0 not 2.1.1 OS: Windows XP Service Pack 2 Build 2600.xpsp_sp2_gdr.0503011519 Submission from: (NULL) (137.208.41.103) In a vanilla R, version 2.3.1 or version 2.3.0 the following crashes: system("gzip.exe") where I did nothing, prior to this command, but change the directory to my other working directory where there's gzip.exe. Same

* checking S3 generic/method consistency ... WARNING Warning: use of NULL environment is deprecated Warning: use of NULL environment is deprecated See section 'Generic functions and methods' of the 'Writing R Extensions' manual. I don't get any other warnings or errors. Can anyone suggest what the problem might be? (R2.3.0, OS X) Thanks, Hadley

Dear Robert, Thanks for your time. I have downloaded Rgraphviz (windows binary) from www.bioconductor.org and put inside R2.3.0 library then i installed from the local zip its says package 'graph' couldnot be loaded. Am i doing the installation correctly? Still the new user. Can you guide me sir? JJ -- Lecturer J. Joshua Thomas KDU College Penang Campus Research Student, University

Hello I'm using logistic regression from the Design library (lrm), then fastbw to undertake a backward selection and create a reduced model, before trying to make predictions against an independent set of data using predict.lrm with the reduced model. I wouldn't normally use this method, but I'm contrasting the results with an AIC/MMI approach. The script contains: # Determine full

Help for help says: The 'topic' argument may also be a function call, to ask for documentation on a corresponding method. See the section on method documentation. and The authors of formal ('S4') methods can provide documentation on specific methods, as well as overall documentation on the methods of a particular function. The

> On Sep 14, 2017, at 12:30 AM, Bonnett, Laura <L.J.Bonnett at liverpool.ac.uk> wrote: > > Dear all, > > I am using the publically available GustoW dataset. The exact version I am using is available here: https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk > > I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT and ANT. I have

I'm trying to learn how to use the lrm() function by simulating data using an old dataset but it's giving me an error I don't understand: (nst$regular already exists) nst$regular<-as.ordered(nst$regular) nst$age<-rnorm(n=942,mean=43.20488,sd=17.03) nst$age<-round(age,digits=0) regform<-regular~age reglrm<-lrm(regform,nst) summary(reglrm) Error in

Hello, I have question regarding the lrm function and estimating the odds ratio between different levels of a factored variable. The following code example illustrates the problem I am having. I have a data set with an outcome variable (0,1) and an input variable (A,B,C). I would like to estimate the effect of C vs B, but when I perform the summary I only get A vs B and A vs C, even though I

Hi Does anyone know whether the rms package provides a confidence interval for the bootstrap-corrected Dxy or c-index? I have fitted a logistic model, and would like to obtain the 95% confidence interval of the bootstrap-corrected area under the ROC curve estimate. Thanks. [[alternative HTML version deleted]]

The code library(Design) f <- lrm(y~x1+x2+x1*x2, data=data) plot(f) produces a plot of log odds vs x2 with 0.95 confidence intervals. How do I get a plot of odds ratios vs x2 instead? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Odds-ratios-from-lrm-plot-tp4033340p4033340.html Sent from the R help mailing list archive at Nabble.com.

Dear all, I'm using the lrm function from the package "Design", and I want to extract the p-values from the results of that function. Given an lrm object constructed as follows : fit <- lrm(Y~(X1+X2+X3+X4+X5+X6+X7)^2, data=dataset) I need the p-values for the coefficients printed by calling "fit". fit$coef (gives a list of only the coefficients) fit$pval, fit$p,

I would appreciate if someone could tell me how to fit a non-intercept model using lrm (and not glm). The -1 in the formula of the glm does not work with lrm. Thanks, Clarissa [[alternative HTML version deleted]]

Dear useR's, I was comparing results for a logistic regression model between different library's. themodel formula is arranged as follows: response ~ (intercept) + value + group OR: glm( response ~ (intercept) + value + group , family=binomial(link='logit')) lrm( response ~ (intercept) + value + group ) ROC( from = response ~ (intercept) + value + group ,

Hi, I am planning to externally validate a logistic prediction model in a new cohort. Outcome is mortality. The betacoefficients were derived from a previous published article. It seems not possible in R to assign fixed beta coefficients to predictors like lrm (death ~ intercept+beta1*var1+beta2*var2...). How do i solve this problem? Thank you in advance. Joey L -- View this message in context: