search for: bergemann

Hi. I would like to use a likelihood-ratio test to compare a linear model (lm()) to another linear model containing the first one to see if the extra factors are needed - but I was unable to find any help on how to do that. Could you help me and tell me what to do? Or tell me where to find help on this topic? Many thanks in advance! Lars

...Here is the command which saves my workspace to my working directory: save.image("H:/Consulting/cmlExprA.RData") And here is the error I get: Error in save(list = ls(envir = .GlobalEnv, all.names = TRUE), file = outfile,: error writing to connection Any assistance? Many thanks, Tracy L. Bergemann, PhD Biostatistics Core University of Minnesota Cancer Center B412-4 Mayo building Office # 626-5408

Hi. I have the following two ecdf plots in one graph: plot( ecdf(....), do.points=FALSE, verticals=TRUE, main=paste("Ecdf of distances ",DIM,sep=""), col="red" ); lines( ecdf(....), do.points=FALSE, verticals=TRUE ); How do I change the color of the resulting graph? Adding col="red" to either plot or lines results in an error

Hey! Could you please take a quick look at what I have done? Somehow I get wrong results using the anova(lm()) combination compared to doing a two way ANOVA by hand. Running: Data<-read.table("Data.txt"); g<-lm(ExM~S1*S2,Data); anova(g); Gives: Analysis of Variance Table Response: ExM Df Sum Sq Mean Sq F value Pr(>F) S1 1 4.3679

Hi. Thanks for your help with my previous question (comparing two lm() models with a maximum likelihood ratio test) I had a look at lrtest from the package lmtest as it has been suggested to me, but I am not 100% sure if that is the right thing to do ... lrtest uses the same log likelihoods as you can extract by hand from lm() with logLik - are this the maximum log likelihoods? How does R

Hi. I tried the following: F<-function(x,y,b1,b2,b3) b1/(1+b2*(x+b3*y)); t<-data.frame(ExM=c(T$ExM,F(T$S1,T$S2,0.2,0.2,51.28205)),S1=rep(T$S1,2),S2=rep(T$S2,2),gr=c(rep(1,length(T$ExM)),rep(2,length(T$ExM)))); library(lattice); wireframe(ExM ~ S1 * S2, data = t, groups=gr); where T is da dataframe like T<-data.frame(S1=...,S2=...,ExM=...) But the resulting response

Hi group, I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R? Thank u so much 4 ur time. [[alternative HTML version deleted]]

...x at level 2 (Godmar Back)   37. please remove me from this list (Curley, Jane)   38. Re: functions to calculate t-stats, etc. for lm.fit objects?       (Marc Schwartz)   39.  Formatting a Table (cvandy)   40. Two-way ANOVA gives different results using anova(lm()) than       doing it by hand (Lars Bergemann)   41. Passing arguments to with() (Tymek Wo?od?ko)   42. Re: functions to calculate t-stats, etc. for lm.fit objects?       (Whit Armstrong)   43. #INCLUDE (Idgarad)   44. Re: Reading from Google Docs (Duncan Murdoch)   45. Re: #INCLUDE (Godmar Back)   46. Comparing GAMMs (Paul Simonin)   47. Re:...