Hello! I have a data frame mysample (sorry for a long way of creating it below - but I need it in this form, and it works). I regress Y onto X1 through X11 - first without weights, then with weights:
regtest1<-lm(Y~., data=mysample[-13])) regtest2<-lm(Y~., data=mysample[-13]),weights=mysample$weight) summary(regtest1) summary(regtest2) Then I calculate Durbin-Watson for both regressions using 2 different packages: library(car) library(lmtest) durbinWatsonTest(regtest1)[2] dwtest(regtest1)$stat durbinWatsonTest(regtest2)[2] dwtest(regtest2)$stat When there are no weights, the Durbin-Watson statistic is the same. But when there are weights, 2 packages give Durbin-Watson different statistics. Anyone knows why? Also, it's interesting that both of them are also different from what SPSS spits out... Thank you! Dimitri ############################################ ### Run the whole code below to create mysample: intercor<-0.3 # intercorrelation among all predictors k<-10 # number of predictors sigma<-matrix(intercor,nrow=k,ncol=k) # matrix of intercorrelations among predictors diag(sigma)<-1 require(mvtnorm) set.seed(123) mypop<-as.data.frame(rmvnorm(n=100000, mean=rep(0,k), sigma=sigma, method="chol")) names(mypop)<-paste("x",1:k,sep="") set.seed(123) mypop$x11<-sample(c(0,1),100000,replace=T) set.seed(123) betas<-round(abs(rnorm(k+1)),2) # desired betas Y<-as.matrix(mypop) %*% betas mypop<-cbind(mypop, Y) rSQR<-.5 VARofY<- mean(apply(as.data.frame(mypop$Y),2,function(x){x^2})) - mean(mypop$Y)^2 mypop$Y<-mypop$Y + rnorm(100000, mean=0, sd=sqrt(VARofY/rSQR-VARofY)) n<-200 set.seed(123) cases.for.sample<-sample(100000,n,replace=F) mysample<-mypop[cases.for.sample,] mysample<-cbind(mysample[k+2],mysample[1:(k+1)]) #dim(sample) weight<-rep(1:10,20);weight<-weight[order(weight)] mysample$weight<-weight -- Dimitri Liakhovitski marketfusionanalytics.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.